Source Code for Module test_suite.system_tests.relax_disp

   1  ############################################################################### 
   2  #                                                                             # 
   3  # Copyright (C) 2006-2014 Edward d'Auvergne                                   # 
   4  # Copyright (C) 2009 Sebastien Morin                                          # 
   5  # Copyright (C) 2013-2014 Troels E. Linnet                                    # 
   6  #                                                                             # 
   7  # This file is part of the program relax (http://www.nmr-relax.com).          # 
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  17  # GNU General Public License for more details.                                # 
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  20  # along with this program.  If not, see <http://www.gnu.org/licenses/>.       # 
  21  #                                                                             # 
  22  ############################################################################### 
  23   
  24  # Python module imports. 
  25  from os import F_OK, access, getcwd, path, sep 
  26  from numpy import array, asarray, exp, median, inf, log, save, std, sum, zeros 
  27  from minfx.generic import generic_minimise 
  28  from random import gauss 
  29  import re, math 
  30  from sys import version_info 
  31  from tempfile import mkdtemp, NamedTemporaryFile 
  32   
  33   
  34  # relax module imports. 
  35  from auto_analyses import relax_disp 
  36  from auto_analyses.relax_disp_repeat_cpmg import DIC_KEY_FORMAT, Relax_disp_rep 
  37  from data_store import Relax_data_store; ds = Relax_data_store() 
  38  import dep_check 
  39  from lib.dispersion.variables import EXP_TYPE_CPMG_DQ, EXP_TYPE_CPMG_MQ, EXP_TYPE_CPMG_PROTON_MQ, EXP_TYPE_CPMG_PROTON_SQ, EXP_TYPE_CPMG_SQ, EXP_TYPE_CPMG_ZQ, EXP_TYPE_LIST, EXP_TYPE_R1RHO, MODEL_B14_FULL, MODEL_CR72, MODEL_CR72_FULL, MODEL_DPL94, MODEL_IT99, MODEL_LIST_ANALYTIC_CPMG, MODEL_LIST_FULL, MODEL_LIST_NUMERIC_CPMG, MODEL_LM63, MODEL_M61, MODEL_M61B, MODEL_MP05, MODEL_NOREX, MODEL_NS_CPMG_2SITE_3D_FULL, MODEL_NS_CPMG_2SITE_EXPANDED, MODEL_NS_CPMG_2SITE_STAR_FULL, MODEL_NS_R1RHO_2SITE, MODEL_NS_R1RHO_3SITE, MODEL_NS_R1RHO_3SITE_LINEAR, MODEL_PARAMS, MODEL_R2EFF, MODEL_TP02, MODEL_TAP03 
  40  from lib.errors import RelaxError 
  41  from lib.io import extract_data, get_file_path, open_read_file 
  42  from lib.spectrum.nmrpipe import show_apod_extract, show_apod_rmsd, show_apod_rmsd_dir_to_files, show_apod_rmsd_to_file 
  43  from pipe_control.mol_res_spin import display_spin, generate_spin_string, return_spin, spin_loop 
  44  from pipe_control.minimise import assemble_scaling_matrix 
  45  from pipe_control.pipes import display 
  46  from specific_analyses.relax_disp.checks import check_missing_r1 
  47  from specific_analyses.relax_disp.estimate_r2eff import estimate_r2eff 
  48  from specific_analyses.relax_disp.data import average_intensity, check_intensity_errors, generate_r20_key, get_curve_type, has_exponential_exp_type, has_r1rho_exp_type, loop_exp_frq, loop_exp_frq_offset_point, loop_exp_frq_offset_point_time, loop_time, return_grace_file_name_ini, return_param_key_from_data, spin_ids_to_containers 
  49  from specific_analyses.relax_disp.data import INTERPOLATE_DISP, INTERPOLATE_OFFSET, X_AXIS_DISP, X_AXIS_W_EFF, X_AXIS_THETA, Y_AXIS_R2_R1RHO, Y_AXIS_R2_EFF 
  50  from specific_analyses.relax_disp.model import models_info, nesting_param 
  51  from specific_analyses.relax_disp.parameters import linear_constraints 
  52  from status import Status; status = Status() 
  53  from test_suite.system_tests.base_classes import SystemTestCase 
  54   
  55  # C modules. 
  56  if dep_check.C_module_exp_fn: 
  57      from specific_analyses.relax_fit.optimisation import func_wrapper, dfunc_wrapper, d2func_wrapper 
  58      from target_functions.relax_fit import jacobian, jacobian_chi2, setup 
  59      # Call the python wrapper function to help with list to numpy array conversion. 
  60      func = func_wrapper 
  61      dfunc = dfunc_wrapper 
  62      d2func = d2func_wrapper 
  63   
  64   
  65 -class Relax_disp(SystemTestCase): 
  66      """Class for testing various aspects specific to relaxation dispersion curve-fitting.""" 
  67   
  68 -    def __init__(self, methodName='runTest'): 
  69          """Skip certain tests if the C modules are non-functional. 
  70   
  71          @keyword methodName:    The name of the test. 
  72          @type methodName:       str 
  73          """ 
  74   
  75          # Execute the base class method. 
  76          super(Relax_disp, self).__init__(methodName) 
  77   
  78          # Tests to skip. 
  79          blacklist = [ 
  80              'test_m61b_data_to_m61b' 
  81          ] 
  82          if methodName in blacklist: 
  83              status.skipped_tests.append([methodName, None, self._skip_type]) 
  84   
  85          # Missing module. 
  86          if not dep_check.C_module_exp_fn: 
  87              # The list of tests to skip. 
  88              to_skip = [ 
  89                  "test_bug_atul_srivastava", 
  90                  "test_bug_21344_sparse_time_spinlock_acquired_r1rho_fail_relax_disp", 
  91                  "test_bug_9999_slow_r1rho_r2eff_error_with_mc", 
  92                  "test_estimate_r2eff_err", 
  93                  "test_estimate_r2eff_err_auto", 
  94                  "test_estimate_r2eff_err_methods", 
  95                  "test_finite_value", 
  96                  "test_exp_fit", 
  97                  "test_m61_exp_data_to_m61", 
  98                  "test_r1rho_kjaergaard_auto", 
  99                  "test_r1rho_kjaergaard_auto_check_graphs", 
 100                  "test_r1rho_kjaergaard_man", 
 101                  "test_r1rho_kjaergaard_missing_r1", 
 102                  "test_value_write_calc_rotating_frame_params_auto_analysis" 
 103              ] 
 104   
 105              # Store in the status object. 
 106              if methodName in to_skip: 
 107                  status.skipped_tests.append([methodName, 'Relax curve-fitting C module', self._skip_type]) 
 108   
 109          # If not scipy.optimize.leastsq. 
 110          if not dep_check.scipy_module: 
 111              # The list of tests to skip. 
 112              to_skip = [ 
 113                  "test_estimate_r2eff_err_methods" 
 114              ] 
 115   
 116              # Store in the status object. 
 117              if methodName in to_skip: 
 118                  status.skipped_tests.append([methodName, 'scipy.optimize.leastsq module', self._skip_type]) 
 119   
 120          # If not NMRPipe showApod program in PATH. 
 121          if not dep_check.showApod_software: 
 122              # The list of tests to skip. 
 123              to_skip = [ 
 124                  "test_show_apod_extract", 
 125                  "test_show_apod_rmsd", 
 126                  "test_show_apod_rmsd_to_file", 
 127                  "test_show_apod_rmsd_dir_to_files" 
 128              ] 
 129   
 130              # Store in the status object. 
 131              if methodName in to_skip: 
 132                  status.skipped_tests.append([methodName, 'NMRPipe showApod program', self._skip_type]) 
 133   
 134          # If not matplotlib module 
 135          if not dep_check.matplotlib_module: 
 136              # The list of tests to skip. 
 137              to_skip = [ 
 138                  "test_repeat_cpmg" 
 139              ] 
 140   
 141              # Store in the status object. 
 142              if methodName in to_skip: 
 143                  status.skipped_tests.append([methodName, 'matplotlib module', self._skip_type]) 
 144   
 145   
 146 -    def setUp(self): 
 147          """Set up for all the functional tests.""" 
 148   
 149          # Create the data pipe. 
 150          self.interpreter.pipe.create('relax_disp', 'relax_disp') 
 151   
 152          # Create a temporary directory for dumping files. 
 153          ds.tmpdir = mkdtemp() 
 154          self.tmpdir = ds.tmpdir 
 155   
 156   
 157 -    def setup_bug_22146_unpacking_r2a_r2b_cluster(self, folder=None, model_analyse=None, places = 7): 
 158          """Setup data for the catch of U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered full dispersion models. 
 159   
 160          @keyword folder:            The name of the folder for the test data. 
 161          @type folder:               str 
 162          @keyword model_analyse:     The name of the model which will be tested. 
 163          @type model_analyse:        str 
 164          """ 
 165   
 166          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen' 
 167   
 168          # Data. 
 169          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_22146_unpacking_r2a_r2b_cluster'+sep+folder 
 170   
 171          ## Experiments 
 172          # Exp 1 
 173          sfrq_1 = 500.0*1E6 
 174          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
 175          time_T2_1 = 0.05 
 176          ncycs_1 = [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 40, 50] 
 177          # Here you define the direct R2eff errors (rad/s), as being added or subtracted for the created R2eff point in the corresponding ncyc cpmg frequence. 
 178          #r2eff_errs_1 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05] 
 179          r2eff_errs_1 = [0.0] * len(ncycs_1) 
 180          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_errs_1] 
 181   
 182          sfrq_2 = 600.0*1E6 
 183          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
 184          time_T2_2 = 0.06 
 185          ncycs_2 = [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 40, 60] 
 186          # Here you define the direct R2eff errors (rad/s), as being added or subtracted for the created R2eff point in the corresponding ncyc cpmg frequence. 
 187          #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05] 
 188          r2eff_errs_2 = [0.0] * len(ncycs_2) 
 189          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_errs_2] 
 190   
 191          sfrq_3 = 700.0*1E6 
 192          r20_key_3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_3) 
 193          time_T2_3 = 0.07 
 194          ncycs_3 = [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 50, 70] 
 195          # Here you define the direct R2eff errors (rad/s), as being added or subtracted for the created R2eff point in the corresponding ncyc cpmg frequence. 
 196          #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05] 
 197          r2eff_errs_3 = [0.0] * len(ncycs_3) 
 198          exp_3 = [sfrq_3, time_T2_3, ncycs_3, r2eff_errs_3] 
 199   
 200          # Collect all exps 
 201          exps = [exp_1, exp_2, exp_3] 
 202   
 203          R20 = [5.1, 5.2, 5.3, 10.1, 10.2, 10.3, 6.1, 6.2, 6.3, 11.1, 11.2, 11.3, 7.1, 7.2, 7.3, 12.1, 12.2, 12.3, 8.1, 8.2, 8.3, 13.1, 13.2, 13.3] 
 204          dw_arr = [1.0, 2.0, 3.0, 4.0] 
 205          pA_arr = [0.9] 
 206          kex_arr = [1000.] 
 207   
 208          spins = [ 
 209                  ['Ala', 1, 'N', {'r2a': {r20_key_1: R20[0], r20_key_2: R20[1], r20_key_3: R20[2]}, 'r2b': {r20_key_1: R20[3], r20_key_2: R20[4], r20_key_3: R20[5]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[0]}], 
 210                  ['Ala', 2, 'N', {'r2a': {r20_key_1: R20[6], r20_key_2: R20[7], r20_key_3: R20[8]}, 'r2b': {r20_key_1: R20[9], r20_key_2: R20[10], r20_key_3: R20[11]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[1]}], 
 211                  ['Ala', 3, 'N', {'r2a': {r20_key_1: R20[12], r20_key_2: R20[13], r20_key_3: R20[14]}, 'r2b': {r20_key_1: R20[15], r20_key_2: R20[16], r20_key_3: R20[17]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[2]}], 
 212                  ['Ala', 4, 'N', {'r2a': {r20_key_1: R20[18], r20_key_2: R20[19], r20_key_3: R20[20]}, 'r2b': {r20_key_1: R20[21], r20_key_2: R20[22], r20_key_3: R20[23]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[3]}], 
 213                  ] 
 214   
 215          # Create the data pipe. 
 216          pipe_name = 'base pipe' 
 217          pipe_type = 'relax_disp' 
 218          pipe_bundle = 'relax_disp' 
 219          self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type, bundle = pipe_bundle) 
 220   
 221          # Generate the sequence. 
 222          for res_name, res_num, spin_name, params in spins: 
 223              self.interpreter.spin.create(res_name=res_name, res_num=res_num, spin_name=spin_name) 
 224   
 225          # Set isotope 
 226          self.interpreter.spin.isotope('15N', spin_id='@N') 
 227   
 228          # Now loop over the experiments, to set the variables in relax. 
 229          exp_ids = [] 
 230          for exp_i in exps: 
 231              sfrq, time_T2, ncycs, r2eff_errs = exp_i 
 232              exp_id = 'CPMG_%3.1f' % (sfrq/1E6) 
 233              exp_ids.append(exp_id) 
 234   
 235              ids = [] 
 236              for ncyc in ncycs: 
 237                  nu_cpmg = ncyc / time_T2 
 238                  cur_id = '%s_%.1f' % (exp_id, nu_cpmg) 
 239                  ids.append(cur_id) 
 240   
 241                  # Set the spectrometer frequency. 
 242                  self.interpreter.spectrometer.frequency(id=cur_id, frq=sfrq) 
 243   
 244                  # Set the experiment type. 
 245                  self.interpreter.relax_disp.exp_type(spectrum_id=cur_id, exp_type=EXP_TYPE_CPMG_SQ) 
 246   
 247                  # Set the relaxation dispersion CPMG constant time delay T (in s). 
 248                  self.interpreter.relax_disp.relax_time(spectrum_id=cur_id, time=time_T2) 
 249   
 250                  # Set the relaxation dispersion CPMG frequencies. 
 251                  self.interpreter.relax_disp.cpmg_setup(spectrum_id=cur_id, cpmg_frq=nu_cpmg) 
 252   
 253          print("\n\nThe experiment IDs are %s." % cdp.spectrum_ids) 
 254   
 255          ### Now do fitting. 
 256          # Change pipe. 
 257   
 258          pipe_name_MODEL = "%s_%s"%(pipe_name, model_analyse) 
 259          self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_MODEL, bundle_to = pipe_bundle) 
 260          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
 261   
 262          # Now read data in. 
 263          for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True): 
 264              exp_id = exp_ids[mi] 
 265              exp_i = exps[mi] 
 266              sfrq, time_T2, ncycs, r2eff_errs = exp_i 
 267   
 268              # Then loop over the spins. 
 269              for res_name, res_num, spin_name, params in spins: 
 270                  cur_spin_id = ":%i@%s"%(res_num, spin_name) 
 271   
 272                  # Define file name 
 273                  file_name = "%s%s.txt" % (exp_id, cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_')) 
 274   
 275                  # Read in the R2eff file to put into spin structure. 
 276                  self.interpreter.relax_disp.r2eff_read_spin(id=exp_id, spin_id=cur_spin_id, file=file_name, dir=data_path, disp_point_col=1, data_col=2, error_col=3) 
 277   
 278          # Then select model. 
 279          self.interpreter.relax_disp.select_model(model=model_analyse) 
 280   
 281          # Then cluster 
 282          self.interpreter.relax_disp.cluster('model_cluster', ":1-100") 
 283   
 284          # Grid search 
 285          low_arr = R20 + dw_arr + pA_arr + kex_arr 
 286          self.interpreter.minimise.grid_search(lower=low_arr, upper=low_arr, inc=1, constraints=True, verbosity=1) 
 287   
 288          # Then loop over the defined spins and read the parameters. 
 289          for i in range(len(spins)): 
 290              res_name, res_num, spin_name, params = spins[i] 
 291              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
 292              cur_spin = return_spin(cur_spin_id) 
 293   
 294              for mo_param in cur_spin.params: 
 295                  print(mo_param) 
 296                  # The R2 is a dictionary, depending on spectrometer frequency. 
 297                  if isinstance(getattr(cur_spin, mo_param), dict): 
 298                      for key, val in list(getattr(cur_spin, mo_param).items()): 
 299                          should_be = params[mo_param][key] 
 300                          print(cur_spin.model, res_name, cur_spin_id, mo_param, key, float(val), should_be) 
 301                          self.assertAlmostEqual(val, should_be) 
 302                  else: 
 303                      should_be = float(params[mo_param]) 
 304                      val = getattr(cur_spin, mo_param) 
 305                      print(cur_spin.model, res_name, cur_spin_id, mo_param, val, should_be) 
 306                      self.assertAlmostEqual(val, should_be) 
 307   
 308              # Test chi2. 
 309              # At this point the chi-squared value at the solution should be zero, as the relaxation data was created with the same parameter values. 
 310              self.assertAlmostEqual(cur_spin.chi2, 0.0, places = places) 
 311   
 312   
 313 -    def setup_r1rho_kjaergaard(self, cluster_ids=[], read_R1=True): 
 314          """Set up the data for the test_r1rho_kjaergaard_*() system tests.""" 
 315   
 316          # The path to the data files. 
 317          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' 
 318   
 319          # Set pipe name, bundle and type. 
 320          ds.pipe_name = 'base pipe' 
 321          ds.pipe_bundle = 'relax_disp' 
 322          ds.pipe_type = 'relax_disp' 
 323   
 324          # Create the data pipe. 
 325          self.interpreter.pipe.create(pipe_name=ds.pipe_name, bundle=ds.pipe_bundle, pipe_type=ds.pipe_type) 
 326   
 327          # Read the spins. 
 328          self.interpreter.spectrum.read_spins(file='1_0_46_0_max_standard.ser', dir=data_path+sep+'peak_lists') 
 329   
 330          # Name the isotope for field strength scaling. 
 331          self.interpreter.spin.isotope(isotope='15N') 
 332   
 333          # Set number of experiments to be used. 
 334          NR_exp = 70 
 335   
 336          # Load the experiments settings file. 
 337          expfile = open(data_path+sep+'exp_parameters_sort.txt', 'r') 
 338          expfileslines = expfile.readlines()[:NR_exp] 
 339          expfile.close() 
 340   
 341          # In MHz 
 342          yOBS = 81.050 
 343          # In ppm 
 344          yCAR = 118.078 
 345          centerPPM_N15 = yCAR 
 346   
 347          ## Read the chemical shift data. 
 348          self.interpreter.chemical_shift.read(file='1_0_46_0_max_standard.ser', dir=data_path+sep+'peak_lists') 
 349   
 350          # The lock power to field, has been found in an calibration experiment. 
 351          spin_lock_field_strengths_Hz = {'35': 431.0, '39': 651.2, '41': 800.5, '43': 984.0, '46': 1341.11, '48': 1648.5} 
 352   
 353          # Apply spectra settings. 
 354          # Count settings 
 355          j = 0 
 356          for i in range(len(expfileslines)): 
 357              line = expfileslines[i] 
 358              if line[0] == "#": 
 359                  continue 
 360              else: 
 361                  # DIRN I deltadof2 dpwr2slock ncyc trim ss sfrq 
 362                  DIRN = line.split()[0] 
 363                  I = int(line.split()[1]) 
 364                  deltadof2 = line.split()[2] 
 365                  dpwr2slock = line.split()[3] 
 366                  ncyc = int(line.split()[4]) 
 367                  trim = float(line.split()[5]) 
 368                  ss = int(line.split()[6]) 
 369                  set_sfrq = float(line.split()[7]) 
 370                  apod_rmsd = float(line.split()[8]) 
 371                  spin_lock_field_strength = spin_lock_field_strengths_Hz[dpwr2slock] 
 372   
 373                  # Calculate spin_lock time 
 374                  time_sl = 2*ncyc*trim 
 375   
 376                  # Define file name for peak list. 
 377                  FNAME = "%s_%s_%s_%s_max_standard.ser"%(I, deltadof2, dpwr2slock, ncyc) 
 378                  sp_id = "%s_%s_%s_%s"%(I, deltadof2, dpwr2slock, ncyc) 
 379   
 380                  # Load the peak intensities. 
 381                  self.interpreter.spectrum.read_intensities(file=FNAME, dir=data_path+sep+'peak_lists', spectrum_id=sp_id, int_method='height') 
 382   
 383                  # Set the peak intensity errors, as defined as the baseplane RMSD. 
 384                  self.interpreter.spectrum.baseplane_rmsd(error=apod_rmsd, spectrum_id=sp_id) 
 385   
 386                  # Set the relaxation dispersion experiment type. 
 387                  self.interpreter.relax_disp.exp_type(spectrum_id=sp_id, exp_type='R1rho') 
 388   
 389                  # Set The spin-lock field strength, nu1, in Hz 
 390                  self.interpreter.relax_disp.spin_lock_field(spectrum_id=sp_id, field=spin_lock_field_strength) 
 391   
 392                  # Calculating the spin-lock offset in ppm, from offsets values provided in Hz. 
 393                  frq_N15_Hz = yOBS * 1E6 
 394                  offset_ppm_N15 = float(deltadof2) / frq_N15_Hz * 1E6 
 395                  omega_rf_ppm = centerPPM_N15 + offset_ppm_N15 
 396   
 397                  # Set The spin-lock offset, omega_rf, in ppm. 
 398                  self.interpreter.relax_disp.spin_lock_offset(spectrum_id=sp_id, offset=omega_rf_ppm) 
 399   
 400                  # Set the relaxation times (in s). 
 401                  self.interpreter.relax_disp.relax_time(spectrum_id=sp_id, time=time_sl) 
 402   
 403                  # Set the spectrometer frequency. 
 404                  self.interpreter.spectrometer.frequency(id=sp_id, frq=set_sfrq, units='MHz') 
 405   
 406                  # Add to counter 
 407                  j += 1 
 408   
 409   
 410          print("Testing the number of settings") 
 411          print("Number of settings iterations is: %s. Number of cdp.exp_type is: %s"%(i, len(cdp.exp_type))) 
 412          self.assertEqual(70, len(expfileslines)) 
 413          self.assertEqual(69, j) 
 414          self.assertEqual(69, len(cdp.exp_type)) 
 415   
 416          # Cluster spins 
 417          for curspin in cluster_ids: 
 418              print("Adding spin %s to cluster"%curspin) 
 419              self.interpreter.relax_disp.cluster('model_cluster', curspin) 
 420   
 421          # De-select for analysis those spins who have not been clustered 
 422          for free_spin in cdp.clustering['free spins']: 
 423              print("Deselecting free spin %s"%free_spin) 
 424              self.interpreter.deselect.spin(spin_id=free_spin, change_all=False) 
 425   
 426   
 427          #Paper         reference values 
 428          #              Resi   Resn         R1_rad_s   R1err_rad_s   R2_rad_s   R2err_rad_s   kEX_rad_s      kEXerr_rad_s  phi_rad2_s2     phierr_rad2_s2    phi_ppm2         phierr_ppm2 
 429          # Scaling rad2_s2 to ppm2: scaling_rad2_s2 = frequency_to_ppm(frq=1/(2*pi), B0=cdp.spectrometer_frq_list[0], isotope='15N')**2 = 3.85167990165e-06 
 430          ds.ref = dict() 
 431          ds.ref[':13@N'] = [13,   'L13N-HN',   1.32394,   0.14687,      8.16007,   1.01237,      13193.82986,   2307.09152,   58703.06446,    22413.09854,      0.2261054135,    0.0863280812] 
 432          ds.ref[':15@N'] = [15,   'R15N-HN',   1.34428,   0.14056,      7.83256,   0.67559,      13193.82986,   2307.09152,   28688.33492,    13480.72253,      0.110498283,     0.051923428] 
 433          ds.ref[':16@N'] = [16,   'T16N-HN',   1.71514,   0.13651,      17.44216,  0.98583,      13193.82986,   2307.09152,   57356.77617,    21892.44205,      0.220919942,     0.084322679] 
 434          ds.ref[':25@N'] = [25,   'Q25N-HN',   1.82412,   0.15809,      9.09447,   2.09215,      13193.82986,   2307.09152,   143111.13431,   49535.80302,      0.5512182797,    0.1907960569] 
 435          ds.ref[':26@N'] = [26,   'Q26N-HN',   1.45746,   0.14127,      10.22801,  0.67116,      13193.82986,   2307.09152,   28187.06876,    13359.01615,      0.1085675662,    0.051454654] 
 436          ds.ref[':28@N'] = [28,   'Q28N-HN',   1.48095,   0.14231,      10.33552,  0.691,        13193.82986,   2307.09152,   30088.0686,     13920.25654,      0.1158896091,    0.0536163723] 
 437          ds.ref[':39@N'] = [39,   'L39N-HN',   1.46094,   0.14514,      8.02194,   0.84649,      13193.82986,   2307.09152,   44130.18538,    18104.55064,      0.1699753481,    0.0697329338] 
 438          ds.ref[':40@N'] = [40,   'M40N-HN',   1.21381,   0.14035,      12.19112,  0.81418,      13193.82986,   2307.09152,   41834.90493,    17319.92156,      0.1611346625,    0.0667107938] 
 439          ds.ref[':41@N'] = [41,   'A41N-HN',   1.29296,   0.14286,      9.29941,   0.66246,      13193.82986,   2307.09152,   26694.8921,     13080.66782,      0.1028201794,    0.0503825453] 
 440          ds.ref[':43@N'] = [43,   'F43N-HN',   1.33626,   0.14352,      12.73816,  1.17386,      13193.82986,   2307.09152,   70347.63797,    26648.30524,      0.2709565833,    0.1026407417] 
 441          ds.ref[':44@N'] = [44,   'I44N-HN',   1.28487,   0.1462,       12.70158,  1.52079,      13193.82986,   2307.09152,   95616.20461,    35307.79817,      0.3682830136,    0.1359943366] 
 442          ds.ref[':45@N'] = [45,   'K45N-HN',   1.59227,   0.14591,      9.54457,   0.95596,      13193.82986,   2307.09152,   53849.7826,     21009.89973,      0.2074121253,    0.0809234085] 
 443          ds.ref[':49@N'] = [49,   'A49N-HN',   1.38521,   0.14148,      4.44842,   0.88647,      13193.82986,   2307.09152,   40686.65286,    18501.20774,      0.1567119631,    0.07126073] 
 444          ds.ref[':52@N'] = [52,   'V52N-HN',   1.57531,   0.15042,      6.51945,   1.43418,      13193.82986,   2307.09152,   93499.92172,    33233.23039,      0.3601317693,    0.1280037656] 
 445          ds.ref[':53@N'] = [53,   'A53N-HN',   1.27214,   0.13823,      4.0705,    0.85485,      13193.82986,   2307.09152,   34856.18636,    17505.02393,      0.1342548725,    0.0674237488] 
 446   
 447          ds.guess = dict() 
 448          ds.guess[':13@N'] = [13,   'L13N-HN',   1.32394,   0.14687,      8.16007,   1.01237,      13193.82986,   2307.09152,   58703.06446,    22413.09854,      0.2261054135,    0.0863280812] 
 449          ds.guess[':15@N'] = [15,   'R15N-HN',   1.34428,   0.14056,      7.83256,   0.67559,      13193.82986,   2307.09152,   28688.33492,    13480.72253,      0.110498283,     0.051923428] 
 450          ds.guess[':16@N'] = [16,   'T16N-HN',   1.71514,   0.13651,      17.44216,  0.98583,      13193.82986,   2307.09152,   57356.77617,    21892.44205,      0.220919942,     0.084322679] 
 451          ds.guess[':25@N'] = [25,   'Q25N-HN',   1.82412,   0.15809,      9.09447,   2.09215,      13193.82986,   2307.09152,   143111.13431,   49535.80302,      0.5512182797,    0.1907960569] 
 452          ds.guess[':26@N'] = [26,   'Q26N-HN',   1.45746,   0.14127,      10.22801,  0.67116,      13193.82986,   2307.09152,   28187.06876,    13359.01615,      0.1085675662,    0.051454654] 
 453          ds.guess[':28@N'] = [28,   'Q28N-HN',   1.48095,   0.14231,      10.33552,  0.691,        13193.82986,   2307.09152,   30088.0686,     13920.25654,      0.1158896091,    0.0536163723] 
 454          ds.guess[':39@N'] = [39,   'L39N-HN',   1.46094,   0.14514,      8.02194,   0.84649,      13193.82986,   2307.09152,   44130.18538,    18104.55064,      0.1699753481,    0.0697329338] 
 455          ds.guess[':40@N'] = [40,   'M40N-HN',   1.21381,   0.14035,      12.19112,  0.81418,      13193.82986,   2307.09152,   41834.90493,    17319.92156,      0.1611346625,    0.0667107938] 
 456          ds.guess[':41@N'] = [41,   'A41N-HN',   1.29296,   0.14286,      9.29941,   0.66246,      13193.82986,   2307.09152,   26694.8921,     13080.66782,      0.1028201794,    0.0503825453] 
 457          ds.guess[':43@N'] = [43,   'F43N-HN',   1.33626,   0.14352,      12.73816,  1.17386,      13193.82986,   2307.09152,   70347.63797,    26648.30524,      0.2709565833,    0.1026407417] 
 458          ds.guess[':44@N'] = [44,   'I44N-HN',   1.28487,   0.1462,       12.70158,  1.52079,      13193.82986,   2307.09152,   95616.20461,    35307.79817,      0.3682830136,    0.1359943366] 
 459          ds.guess[':45@N'] = [45,   'K45N-HN',   1.59227,   0.14591,      9.54457,   0.95596,      13193.82986,   2307.09152,   53849.7826,     21009.89973,      0.2074121253,    0.0809234085] 
 460          ds.guess[':49@N'] = [49,   'A49N-HN',   1.38521,   0.14148,      4.44842,   0.88647,      13193.82986,   2307.09152,   40686.65286,    18501.20774,      0.1567119631,    0.07126073] 
 461          ds.guess[':52@N'] = [52,   'V52N-HN',   1.57531,   0.15042,      6.51945,   1.43418,      13193.82986,   2307.09152,   93499.92172,    33233.23039,      0.3601317693,    0.1280037656] 
 462          ds.guess[':53@N'] = [53,   'A53N-HN',   1.27214,   0.13823,      4.0705,    0.85485,      13193.82986,   2307.09152,   34856.18636,    17505.02393,      0.1342548725,    0.0674237488] 
 463   
 464          # Assign guess values. 
 465          for spin, spin_id in spin_loop(return_id=True): 
 466              if spin_id in cluster_ids: 
 467                  print("spin_id %s in cluster ids"%(spin_id)) 
 468                  spin.kex = ds.guess[spin_id][6] 
 469                  spin.phi_ex = ds.guess[spin_id][10] 
 470              else: 
 471                  print("spin_id %s NOT in cluster ids"%(spin_id)) 
 472   
 473          if read_R1: 
 474              # Read the R1 data 
 475              self.interpreter.relax_data.read(ri_id='R1', ri_type='R1', frq=cdp.spectrometer_frq_list[0], file='R1_fitted_values.txt', dir=data_path, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5, data_col=6, error_col=7) 
 476   
 477   
 478 -    def setup_hansen_cpmg_data(self, model=None): 
 479          """Set up the data for the test_hansen_cpmg_data_*() system tests. 
 480   
 481          @keyword model: The name of the model which will be tested. 
 482          @type model:    str 
 483          """ 
 484   
 485          # Create the data pipe and load the base data. 
 486          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen' 
 487          self.interpreter.pipe.create(pipe_name='base pipe', pipe_type='relax_disp') 
 488          self.interpreter.results.read(data_path+sep+'base_pipe') 
 489          self.interpreter.deselect.spin(':4') 
 490   
 491          # Set the nuclear isotope data. 
 492          self.interpreter.spin.isotope('15N') 
 493   
 494          # Create the R2eff data pipe and load the results. 
 495          self.interpreter.pipe.create(pipe_name='R2eff - relax_disp', pipe_type='relax_disp') 
 496          self.interpreter.pipe.switch(pipe_name='R2eff - relax_disp') 
 497          self.interpreter.results.read(data_path+sep+'r2eff_pipe') 
 498          self.interpreter.deselect.spin(':4') 
 499   
 500          # The model data pipe. 
 501          pipe_name = "%s - relax_disp" % model 
 502          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
 503          self.interpreter.pipe.switch(pipe_name=pipe_name) 
 504   
 505          # Set the model. 
 506          self.interpreter.relax_disp.select_model(model=model) 
 507   
 508          # Copy the data. 
 509          self.interpreter.value.copy(pipe_from='R2eff - relax_disp', pipe_to=pipe_name, param='r2eff') 
 510   
 511   
 512 -    def setup_kteilum_fmpoulsen_makke_cpmg_data(self, model=None, expfolder=None): 
 513          """Set up the data for the test_kteilum_fmpoulsen_makke_cpmg_data_*() system tests. 
 514   
 515          @keyword model: The name of the model which will be tested. 
 516          @type model:    str 
 517          """ 
 518   
 519          # Create the data pipe and load the base data. 
 520          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'KTeilum_FMPoulsen_MAkke_2006'+sep+expfolder 
 521          self.interpreter.pipe.create(pipe_name='base pipe', pipe_type='relax_disp') 
 522          self.interpreter.results.read(data_path+sep+'ini_setup_trunc') 
 523   
 524          # Create the R2eff data pipe and load the results. 
 525          self.interpreter.pipe.create(pipe_name='R2eff', pipe_type='relax_disp') 
 526          self.interpreter.pipe.switch(pipe_name='R2eff') 
 527          self.interpreter.results.read(data_path+sep+'r2eff_pipe_trunc') 
 528   
 529          # The model data pipe. 
 530          pipe_name = "%s - relax_disp" % model 
 531          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
 532          self.interpreter.pipe.switch(pipe_name=pipe_name) 
 533   
 534          # Set the model. 
 535          self.interpreter.relax_disp.select_model(model=model) 
 536   
 537          # Copy the data. 
 538          self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff') 
 539   
 540   
 541 -    def setup_korzhnev_2005_data(self, data_list=[]): 
 542          """Set up the data for the test_korzhnev_2005_data_*() system tests using the 'NS MMQ 2-site' model. 
 543   
 544          This loads the proton-heteronuclear SQ, ZQ, DQ, and MQ (MMQ) data from: 
 545   
 546              - Dmitry M. Korzhnev, Philipp Neudecker, Anthony Mittermaier, Vladislav Yu. Orekhov, and Lewis E. Kay (2005)  Multiple-site exchange in proteins studied with a suite of six NMR relaxation dispersion experiments: An application to the folding of a Fyn SH3 domain mutant.  127, 15602-15611 (U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}). 
 547   
 548          It consists of the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
 549   
 550   
 551          @keyword data_list: The list of data to load.  It can contain 'SQ', '1H SQ', 'ZQ', 'DQ', 'MQ', and '1H MQ'. 
 552          @type data_list:    list of str 
 553          """ 
 554   
 555          # Create the data pipe and load the base data. 
 556          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Korzhnev_et_al_2005' 
 557          self.interpreter.pipe.create(pipe_name='Korzhnev et al., 2005', pipe_type='relax_disp') 
 558   
 559          # Create the spin system. 
 560          self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='H') 
 561          self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='N') 
 562          self.interpreter.spin.element('H', spin_id='@H') 
 563          self.interpreter.spin.element('N', spin_id='@N') 
 564          self.interpreter.spin.isotope('1H', spin_id='@H') 
 565          self.interpreter.spin.isotope('15N', spin_id='@N') 
 566   
 567          # Define the magnetic dipole-dipole relaxation interaction. 
 568          self.interpreter.interatom.define(spin_id1=':9@N', spin_id2=':9@H', direct_bond=True) 
 569   
 570          # The spectral data - experiment ID, R2eff file name, experiment type, spin ID string, spectrometer frequency in Hertz, relaxation time. 
 571          data = [ 
 572              ['1H SQ', '1H_SQ_CPMG_500_MHz',  'hs_500.res', EXP_TYPE_CPMG_PROTON_SQ, ':9@H', 500e6, 0.03], 
 573              ['1H SQ', '1H_SQ_CPMG_600_MHz',  'hs_600.res', EXP_TYPE_CPMG_PROTON_SQ, ':9@H', 600e6, 0.03], 
 574              ['1H SQ', '1H_SQ_CPMG_800_MHz',  'hs_800.res', EXP_TYPE_CPMG_PROTON_SQ, ':9@H', 800e6, 0.03], 
 575              ['SQ',    '15N_SQ_CPMG_500_MHz', 'ns_500.res', EXP_TYPE_CPMG_SQ,        ':9@N', 500e6, 0.04], 
 576              ['SQ',    '15N_SQ_CPMG_600_MHz', 'ns_600.res', EXP_TYPE_CPMG_SQ,        ':9@N', 600e6, 0.04], 
 577              ['SQ',    '15N_SQ_CPMG_800_MHz', 'ns_800.res', EXP_TYPE_CPMG_SQ,        ':9@N', 800e6, 0.04], 
 578              ['DQ',    '15N_DQ_CPMG_500_MHz', 'dq_500.res', EXP_TYPE_CPMG_DQ,        ':9@N', 500e6, 0.03], 
 579              ['DQ',    '15N_DQ_CPMG_600_MHz', 'dq_600.res', EXP_TYPE_CPMG_DQ,        ':9@N', 600e6, 0.03], 
 580              ['DQ',    '15N_DQ_CPMG_800_MHz', 'dq_800.res', EXP_TYPE_CPMG_DQ,        ':9@N', 800e6, 0.03], 
 581              ['ZQ',    '15N_ZQ_CPMG_500_MHz', 'zq_500.res', EXP_TYPE_CPMG_ZQ,        ':9@N', 500e6, 0.03], 
 582              ['ZQ',    '15N_ZQ_CPMG_600_MHz', 'zq_600.res', EXP_TYPE_CPMG_ZQ,        ':9@N', 600e6, 0.03], 
 583              ['ZQ',    '15N_ZQ_CPMG_800_MHz', 'zq_800.res', EXP_TYPE_CPMG_ZQ,        ':9@N', 800e6, 0.03], 
 584              ['1H MQ', '1H_MQ_CPMG_500_MHz',  'hm_500.res', EXP_TYPE_CPMG_PROTON_MQ, ':9@H', 500e6, 0.02], 
 585              ['1H MQ', '1H_MQ_CPMG_600_MHz',  'hm_600.res', EXP_TYPE_CPMG_PROTON_MQ, ':9@H', 600e6, 0.02], 
 586              ['1H MQ', '1H_MQ_CPMG_800_MHz',  'hm_800.res', EXP_TYPE_CPMG_PROTON_MQ, ':9@H', 800e6, 0.02], 
 587              ['MQ',    '15N_MQ_CPMG_500_MHz', 'nm_500.res', EXP_TYPE_CPMG_MQ,        ':9@N', 500e6, 0.02], 
 588              ['MQ',    '15N_MQ_CPMG_600_MHz', 'nm_600.res', EXP_TYPE_CPMG_MQ,        ':9@N', 600e6, 0.02], 
 589              ['MQ',    '15N_MQ_CPMG_800_MHz', 'nm_800.res', EXP_TYPE_CPMG_MQ,        ':9@N', 800e6, 0.02] 
 590          ] 
 591          cpmg_frqs_1h_sq = [67.0, 133.0, 267.0, 400.0, 533.0, 667.0, 800.0, 933.0, 1067.0, 1600.0, 2133.0, 2667.0] 
 592          cpmg_frqs_sq = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 450.0, 500.0, 600.0, 700.0, 800.0, 900.0, 1000.0] 
 593          cpmg_frqs_dq = [33.0, 67.0, 133.0, 200.0, 267.0, 333.0, 400.0, 467.0, 533.0, 667.0, 800.0, 933.0, 1067.0] 
 594          cpmg_frqs_zq = [33.0, 67.0, 133.0, 200.0, 267.0, 333.0, 400.0, 467.0, 533.0, 667.0, 800.0, 933.0, 1067.0] 
 595          cpmg_frqs_1h_mq = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 400.0, 500.0, 600.0, 700.0, 800.0, 1000.0, 1500.0, 2000.0, 2500.0] 
 596          cpmg_frqs_mq = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 500.0, 600.0, 700.0, 800.0, 900.0, 1000.0] 
 597   
 598          # Loop over the files, reading in the data. 
 599          for data_type, id, file, exp_type, spin_id, H_frq, relax_time in data: 
 600              # Skip undesired data. 
 601              if data_type not in data_list: 
 602                  continue 
 603   
 604              # Alias the CPMG frequencies. 
 605              if data_type == 'SQ': 
 606                  cpmg_frqs = cpmg_frqs_sq 
 607              elif data_type == '1H SQ': 
 608                  cpmg_frqs = cpmg_frqs_1h_sq 
 609              elif data_type == 'DQ': 
 610                  cpmg_frqs = cpmg_frqs_dq 
 611              elif data_type == 'ZQ': 
 612                  cpmg_frqs = cpmg_frqs_zq 
 613              elif data_type == '1H MQ': 
 614                  cpmg_frqs = cpmg_frqs_1h_mq 
 615              elif data_type == 'MQ': 
 616                  cpmg_frqs = cpmg_frqs_mq 
 617   
 618              # Loop over each CPMG frequency. 
 619              for cpmg_frq in cpmg_frqs: 
 620                  # The id. 
 621                  new_id = "%s_%s" % (id, cpmg_frq) 
 622   
 623                  # Set the NMR field strength. 
 624                  self.interpreter.spectrometer.frequency(id=new_id, frq=H_frq) 
 625   
 626                  # Set the relaxation dispersion experiment type. 
 627                  self.interpreter.relax_disp.exp_type(spectrum_id=new_id, exp_type=exp_type) 
 628   
 629                  # Relaxation dispersion CPMG constant time delay T (in s). 
 630                  self.interpreter.relax_disp.relax_time(spectrum_id=new_id, time=relax_time) 
 631   
 632                  # Set the CPMG frequency. 
 633                  self.interpreter.relax_disp.cpmg_setup(spectrum_id=new_id, cpmg_frq=cpmg_frq) 
 634   
 635              # Read the R2eff data. 
 636              self.interpreter.relax_disp.r2eff_read_spin(id=id, file=file, dir=data_path, spin_id=spin_id, disp_point_col=1, data_col=2, error_col=3) 
 637   
 638          # Change the model. 
 639          self.interpreter.relax_disp.select_model('NS MMQ 2-site') 
 640   
 641   
 642 -    def setup_sod1wt_t25(self, pipe_name, pipe_type, pipe_name_r2eff, select_spin_index): 
 643          """Setup of data SOD1-WT CPMG. From paper at U{http://dx.doi.org/10.1073/pnas.0907387106}. 
 644   
 645          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
 646          'SOD1-WT' CPMG data to the CR72 dispersion model. 
 647   
 648          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
 649          Data is for experiment at 25 degree Celcius. 
 650          """ 
 651   
 652          # Create the data pipe and load the base data. 
 653          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'sod1wt_t25' 
 654   
 655          # Set experiment settings. sfrq, time_T2, ncyc 
 656          Exps = [ 
 657          ["600MHz", "Z_A", 599.8908617*1E6, 0.06, [28, 0, 4, 32, 60, 2, 10, 16, 8, 20, 50, 18, 40, 6, 12, 0, 24], ["Z_A1", "Z_A15"] ], 
 658          ["500MHz", "Z_B", 499.862139*1E6, 0.04, [20, 0, 16, 10, 36, 2, 12, 4, 22, 18, 40, 14, 26, 8, 32, 24, 6, 28, 0], ["Z_B1", "Z_B18"] ] ] 
 659   
 660          # Create base pipe 
 661          self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type) 
 662   
 663          # Loop throug experiments 
 664          id_lists = [] 
 665          for folder, key, sfrq, time_T2, ncycs, rep_ncyss in Exps: 
 666              # Read spins 
 667              self.interpreter.spectrum.read_spins(file="128_FT.ser", dir=data_path+sep+folder) 
 668              self.interpreter.spectrum.read_spins(file="128_FT.ser", dir=data_path+sep+folder) 
 669   
 670              # Make spectrum id list 
 671              id_list = list(key+str(i) for i in range(len(ncycs))) 
 672              id_lists.append(id_list) 
 673   
 674              # Read intensities 
 675              self.interpreter.spectrum.read_intensities(file="128_FT.ser", dir=data_path+sep+folder, int_method='height', spectrum_id=id_list, int_col=list(range(len(id_list))) ) 
 676   
 677              # Loop over experiments 
 678              for i in range(len(ncycs)): 
 679                  ncyc = ncycs[i] 
 680                  vcpmg = ncyc/time_T2 
 681   
 682                  # Test if spectrum is a reference 
 683                  if float(vcpmg) == 0.0: 
 684                      vcpmg = None 
 685                  else: 
 686                      vcpmg = round(float(vcpmg), 3) 
 687   
 688                  # Set current id 
 689                  current_id = id_list[i] 
 690   
 691                  # Set the current experiment type. 
 692                  self.interpreter.relax_disp.exp_type(spectrum_id=current_id, exp_type='SQ CPMG') 
 693   
 694                  # Set the NMR field strength of the spectrum. 
 695                  self.interpreter.spectrometer.frequency(id=current_id, frq=sfrq, units='Hz') 
 696   
 697                  # Relaxation dispersion CPMG constant time delay T (in s). 
 698                  self.interpreter.relax_disp.relax_time(spectrum_id=current_id, time=time_T2) 
 699   
 700                  # Set the relaxation dispersion CPMG frequencies. 
 701                  self.interpreter.relax_disp.cpmg_setup(spectrum_id=current_id, cpmg_frq=vcpmg) 
 702   
 703          # Define replicated 
 704          self.interpreter.spectrum.replicated(spectrum_ids=Exps[0][5]) 
 705          self.interpreter.spectrum.replicated(spectrum_ids=Exps[1][5]) 
 706   
 707          # Perform error analysis 
 708          self.interpreter.spectrum.error_analysis(subset=id_lists[0]) 
 709          self.interpreter.spectrum.error_analysis(subset=id_lists[1]) 
 710   
 711          # Define isotope 
 712          self.interpreter.spin.isotope(isotope='15N') 
 713   
 714          ############# 
 715   
 716          # Define the 64 residues which was used for Global fitting 
 717          glob_assn = ["G10N-H", "D11N-H", "Q15N-H", "G16N-H", "G37N-H", "G41N-H", "L42N-H", "H43N-H", "H46N-H", "V47N-H", "E49N-H", 
 718          "E50N-H", "E51N-H", "N53N-H", "T54N-H", "G56N-H", "C57N-H", "T58N-H", "G61N-H", "H63aN-H", "F64aN-H", "N65aN-H", 
 719          "L67N-H", "S68N-H", "K70N-H", "G72N-H", "G73N-H", "K75N-H", "E78N-H", "R79N-H", "H80N-H", "V81N-H", "G82N-H", 
 720          "G85N-H", "N86N-H", "V87N-H", "S102N-H", "V103N-H", "I104N-H", "S105N-H", "A111N-H", "I112N-H", "R115N-H", 
 721          "V118N-H", "E121N-H", "A123N-H", "L126N-H", "G127N-H", "K128N-H", "G129N-H", "G130N-H", "N131N-H", "E133N-H", 
 722          "S134N-H", "T135N-H", "T137N-H", "G138N-H", "N139N-H", "A140N-H", "G141N-H", "S142N-H", "R143N-H", "C146N-H", "G147N-H"] 
 723   
 724          # Test number of global 
 725          self.assertEqual(64, len(glob_assn )) 
 726   
 727          ## Turn assignments into relax spin ids. 
 728          # Define regular expression search 
 729          r = re.compile("([a-zA-Z]+)([0-9]+)([a-zA-Z]+)") 
 730   
 731          # Create list to hold regular expression search 
 732          relax_glob_ids = [] 
 733   
 734          # Loop over assignments 
 735          for assn in glob_assn: 
 736              # Make match for the regular search 
 737              m = r.match(assn) 
 738              # Convert to relax spin string 
 739              relax_string = ":%s@%s"%(m.group(2), m.group(3)) 
 740   
 741              # Save the relax spin string and the regular search 
 742              relax_glob_ids.append([m.group(0), m.group(1), m.group(2), m.group(3), relax_string]) 
 743   
 744          ############# Deselect all spins, and select few spins 
 745   
 746          ## Deselect all spins, and select a few for analysis 
 747          self.interpreter.deselect.all() 
 748   
 749          # Select few spins 
 750          for i in select_spin_index: 
 751              self.interpreter.select.spin(spin_id=relax_glob_ids[i][4], change_all=False) 
 752   
 753          ############## 
 754   
 755          # Prepare for R2eff calculation 
 756          self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_r2eff) 
 757          self.interpreter.pipe.switch(pipe_name=pipe_name_r2eff) 
 758   
 759          # Select model for points calculation 
 760          MODEL = "R2eff" 
 761          self.interpreter.relax_disp.select_model(model=MODEL) 
 762          # Calculate R2eff values 
 763          self.interpreter.minimise.calculate(verbosity=1) 
 764   
 765   
 766 -    def setup_missing_r1_spins(self): 
 767          """Function for setting up a few spins for the given pipe.""" 
 768   
 769          # Path to file. 
 770          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' 
 771   
 772          # File with spins. 
 773          file = open(data_path+sep+'R1_fitted_values.txt') 
 774          lines = file.readlines() 
 775          file.close() 
 776   
 777          for i, line in enumerate(lines): 
 778              # Make the string test 
 779              line_split = line.split() 
 780   
 781              if line_split[0] == "#": 
 782                  continue 
 783   
 784              mol_name = line_split[0] 
 785              mol_name = None 
 786              res_num = int(line_split[1]) 
 787              res_name = line_split[2] 
 788              spin_num = line_split[3] 
 789              spin_num = None 
 790              spin_name = line_split[4] 
 791   
 792              # Create the spin. 
 793              self.interpreter.spin.create(spin_name=spin_name, spin_num=spin_num, res_name=res_name, res_num=res_num, mol_name=mol_name) 
 794   
 795   
 796 -    def setup_tp02_data_to_ns_r1rho_2site(self, clustering=False): 
 797          """Setup data for the test of relaxation dispersion 'NS R1rho 2-site' model fitting against the 'TP02' test data.""" 
 798   
 799          # Reset. 
 800          self.interpreter.reset() 
 801   
 802          # Create the data pipe and load the base data. 
 803          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r1rho_off_res_tp02' 
 804          self.interpreter.state.load(data_path+sep+'r2eff_values') 
 805   
 806          # The model data pipe. 
 807          model = 'NS R1rho 2-site' 
 808          pipe_name = "%s - relax_disp" % model 
 809          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
 810          self.interpreter.pipe.switch(pipe_name=pipe_name) 
 811   
 812          # Set the model. 
 813          self.interpreter.relax_disp.select_model(model=model) 
 814   
 815          # Copy the data. 
 816          self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff') 
 817   
 818          # Alias the spins. 
 819          spin1 = cdp.mol[0].res[0].spin[0] 
 820          spin2 = cdp.mol[0].res[1].spin[0] 
 821   
 822          # The R20 keys. 
 823          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
 824          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
 825   
 826          # Set the initial parameter values. 
 827          spin1.r2 = {r20_key1: 9.9963793866185, r20_key2: 15.0056724422684} 
 828          spin1.pA = 0.779782428085762 
 829          spin1.dw = 7.57855284496424 
 830          spin1.kex = 1116.7911285203 
 831          spin2.r2 = {r20_key1: 11.9983346935434, r20_key2: 18.0076097513337} 
 832          spin2.pA = 0.826666229688602 
 833          spin2.dw = 9.5732624231366 
 834          spin2.kex = 1380.46162655657 
 835   
 836          # Test the values when clustering. 
 837          if clustering: 
 838              self.interpreter.relax_disp.cluster(cluster_id='all', spin_id=":1-100") 
 839   
 840          # Low precision optimisation. 
 841          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
 842   
 843          # Printout. 
 844          print("\n\nOptimised parameters:\n") 
 845          print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 
 846          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 
 847          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 
 848          print("%-20s %20.15g %20.15g" % ("pA", spin1.pA, spin2.pA)) 
 849          print("%-20s %20.15g %20.15g" % ("dw", spin1.dw, spin2.dw)) 
 850          print("%-20s %20.15g %20.15g" % ("kex", spin1.kex, spin2.kex)) 
 851          print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 
 852   
 853   
 854 -    def test_baldwin_synthetic(self): 
 855          """Test synthetic data of Andrew J. Baldwin B14 model  whereby the simplification R20A = R20B is assumed. 
 856   
 857          Support requst sr #3154 U{https://gna.org/support/index.php?3154}. 
 858   
 859          This uses the synthetic data from paper U{DOI: 10.1016/j.jmr.2014.02.023 <http://dx.doi.org/10.1016/j.jmr.2014.02.023>} with R20A, R20B = 2. rad/s. 
 860          """ 
 861   
 862          # The path to the data files. 
 863          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Baldwin_2014' 
 864   
 865          # Create pipe 
 866          pipe_name = 'base pipe' 
 867          pipe_type = 'relax_disp' 
 868          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
 869   
 870          # Create base pipe 
 871          self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type) 
 872   
 873          # Generate the sequence. 
 874          self.interpreter.spin.create(res_name='Ala', res_num=1, spin_name='H') 
 875   
 876          # Define the isotope. 
 877          self.interpreter.spin.isotope('1H', spin_id='@H') 
 878   
 879          # Build the experiment IDs. 
 880          # Number of cpmg cycles (1 cycle = delay/180/delay/delay/180/delay) 
 881          ncycs = [2, 4, 8, 10, 20, 40, 500] 
 882          ids = [] 
 883          for ncyc in ncycs: 
 884              ids.append('CPMG_%s' % ncyc) 
 885   
 886          print("\n\nThe experiment IDs are %s." % ids) 
 887   
 888          # Set up the metadata for the experiments. 
 889          # This value is used in Baldwin.py. It is the 1H Larmor frequency. 
 890          sfrq = 200. * 1E6 
 891   
 892          # Total time of CPMG block. 
 893          Trelax = 0.04 
 894   
 895          # First set the 
 896          for i in range(len(ids)): 
 897              id = ids[i] 
 898              # Set the spectrometer frequency. 
 899              self.interpreter.spectrometer.frequency(id=id, frq=sfrq) 
 900   
 901              # Set the experiment type. 
 902              self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 
 903   
 904              # Set the relaxation dispersion CPMG constant time delay T (in s). 
 905              self.interpreter.relax_disp.relax_time(spectrum_id=id, time=Trelax) 
 906   
 907              # Set the relaxation dispersion CPMG frequencies. 
 908              ncyc = ncycs[i] 
 909              nu_cpmg = ncyc / Trelax 
 910              self.interpreter.relax_disp.cpmg_setup(spectrum_id=id, cpmg_frq=nu_cpmg) 
 911   
 912          # Prepare for R2eff reading. 
 913          self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_r2eff) 
 914          self.interpreter.pipe.switch(pipe_name=pipe_name_r2eff) 
 915   
 916          # Try reading the R2eff file. 
 917          self.interpreter.relax_disp.r2eff_read_spin(id="CPMG", file="test_r2a_eq_r2b_w_error.out", dir=data_path, spin_id=':1@H', disp_point_col=1, data_col=2, error_col=3) 
 918   
 919          # Check the global data. 
 920          data = [ 
 921              ['cpmg_frqs', {'CPMG_20': 500.0, 'CPMG_10': 250.0, 'CPMG_40': 1000.0, 'CPMG_4': 100.0, 'CPMG_2': 50.0, 'CPMG_500': 12500.0, 'CPMG_8': 200.0}], 
 922              ['cpmg_frqs_list', list(array(ncycs)/Trelax) ], 
 923              ['dispersion_points', len(ncycs)], 
 924              ['exp_type', {'CPMG_20': 'SQ CPMG', 'CPMG_10': 'SQ CPMG', 'CPMG_40': 'SQ CPMG', 'CPMG_4': 'SQ CPMG', 'CPMG_2': 'SQ CPMG', 'CPMG_500': 'SQ CPMG', 'CPMG_8': 'SQ CPMG'}], 
 925              ['exp_type_list', ['SQ CPMG']], 
 926              ['spectrometer_frq', {'CPMG_20': 200000000.0, 'CPMG_10': 200000000.0, 'CPMG_40': 200000000.0, 'CPMG_4': 200000000.0, 'CPMG_2': 200000000.0, 'CPMG_500': 200000000.0, 'CPMG_8': 200000000.0}], 
 927              ['spectrometer_frq_count', 1], 
 928              ['spectrometer_frq_list', [sfrq]], 
 929              ['spectrum_ids', ['CPMG_2', 'CPMG_4', 'CPMG_8', 'CPMG_10', 'CPMG_20', 'CPMG_40', 'CPMG_500']] 
 930          ] 
 931          for name, value in data: 
 932              # Does it exist? 
 933              self.assert_(hasattr(cdp, name)) 
 934   
 935              # Check the object. 
 936              obj = getattr(cdp, name) 
 937              if not isinstance(data, dict): 
 938                  self.assertEqual(obj, value) 
 939   
 940              # Check the global dictionary data. 
 941              else: 
 942                  for id in ids: 
 943                      self.assertEqual(obj[id], value[id]) 
 944   
 945          # Check the spin data. 
 946          n_data = [ 
 947              [ 50.000000, 10.367900, 0.1], 
 948              [ 100.000000, 10.146849, 0.1], 
 949              [ 200.000000, 9.765987, 0.1], 
 950              [ 250.000000, 9.409789, 0.1], 
 951              [ 500.000000, 5.829819, 0.1], 
 952              [ 1000.000000, 3.191928, 0.1], 
 953              [ 12500.000000, 2.008231, 0.1] 
 954          ] 
 955          for disp_point, value, error in n_data: 
 956              id = 'sq_cpmg_200.00000000_0.000_%.3f' % disp_point 
 957              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff[id], value) 
 958              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff_err[id], error) 
 959   
 960          # Generate r20 key. 
 961          r20_key = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq) 
 962   
 963          ## Now prepare for MODEL calculation. 
 964          MODEL = "B14" 
 965   
 966          # Change pipe. 
 967          pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 
 968          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
 969          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
 970   
 971          # Then select model. 
 972          self.interpreter.relax_disp.select_model(model=MODEL) 
 973   
 974          # Store grid and minimisations results. 
 975          grid_results = [] 
 976          mini_results = [] 
 977   
 978          # The grid search size (the number of increments per dimension). 
 979          # If None, use the default values. 
 980          #GRID = None 
 981          GRID = 13 
 982          # Perform Grid Search. 
 983          if GRID: 
 984              # Set the R20 parameters in the default grid search using the minimum R2eff value. 
 985              # This speeds it up considerably. 
 986              self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
 987   
 988              # Then do grid search. 
 989              self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID, constraints=True, verbosity=1) 
 990   
 991              # If no Grid search, set the default values. 
 992          else: 
 993              for param in MODEL_PARAMS[MODEL]: 
 994                  self.interpreter.value.set(param=param, index=None) 
 995                  # Do a grid search, which will store the chi2 value. 
 996              self.interpreter.minimise.grid_search(lower=None, upper=None, inc=1, constraints=True, verbosity=1) 
 997   
 998          # Store result. 
 999          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1000              grid_results.append([spin.r2[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
1001   
1002          ## Now do minimisation. 
1003          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
1004          set_func_tol = 1e-10 
1005          set_max_iter = 1000 
1006          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
1007   
1008          # Store result. 
1009          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1010              mini_results.append([spin.r2[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
1011   
1012          # Print results. 
1013          for i in range(len(grid_results)): 
1014              g_r2, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 
1015              m_r2, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 
1016              print("GRID %s r2=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(g_spin_id, g_r2, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 
1017              print("MIN  %s r2=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(m_spin_id, m_r2, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 
1018   
1019          # Reference values from Baldwin.py. 
1020          # Exchange rate = k+ + k- (s-1) 
1021          kex = 1000. 
1022          # Fractional population of excited state k+/kex 
1023          pb = 0.01 
1024          # deltaOmega in ppm 
1025          dw_ppm = 2. 
1026          #relaxation rate of ground (s-1) 
1027          R2g = 2. 
1028          #relaxation rate of excited (s-1) 
1029          R2e = 2. 
1030   
1031          # Test the parameters which created the data. 
1032          # This is for the 1H spin. 
1033          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2[r20_key], R2g, 6) 
1034   
1035          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].dw, dw_ppm, 6) 
1036          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].pA, 1-pb, 8) 
1037          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].kex, kex, 3) 
1038   
1039   
1040 -    def test_baldwin_synthetic_full(self): 
1041          """Test synthetic data of Andrew J. Baldwin B14 model. Support requst sr #3154 U{https://gna.org/support/index.php?3154}. 
1042   
1043          This uses the synthetic data from paper U{DOI: 10.1016/j.jmr.2014.02.023 <http://dx.doi.org/10.1016/j.jmr.2014.02.023>}. 
1044          """ 
1045   
1046          # The path to the data files. 
1047          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Baldwin_2014' 
1048   
1049          # Create pipe 
1050          pipe_name = 'base pipe' 
1051          pipe_type = 'relax_disp' 
1052          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
1053   
1054          # Create base pipe 
1055          self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type) 
1056   
1057          # Generate the sequence. 
1058          # Generate both a 1H spin, and 15N spin. 
1059          self.interpreter.spin.create(res_name='Ala', res_num=1, spin_name='H') 
1060   
1061          # Define the isotope. 
1062          self.interpreter.spin.isotope('1H', spin_id='@H') 
1063   
1064          # Build the experiment IDs. 
1065          # Number of cpmg cycles (1 cycle = delay/180/delay/delay/180/delay) 
1066          ncycs = [2, 4, 8, 10, 20, 40, 500] 
1067          ids = [] 
1068          for ncyc in ncycs: 
1069              ids.append('CPMG_%s' % ncyc) 
1070   
1071          print("\n\nThe experiment IDs are %s." % ids) 
1072   
1073          # Set up the metadata for the experiments. 
1074          # This value is used in Baldwin.py. It is the 1H Larmor frequency. 
1075          sfrq = 200. * 1E6 
1076   
1077          # Total time of CPMG block. 
1078          Trelax = 0.04 
1079   
1080          # First set the 
1081          for i in range(len(ids)): 
1082              id = ids[i] 
1083              # Set the spectrometer frequency. 
1084              self.interpreter.spectrometer.frequency(id=id, frq=sfrq) 
1085   
1086              # Set the experiment type. 
1087              self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 
1088   
1089              # Set the relaxation dispersion CPMG constant time delay T (in s). 
1090              self.interpreter.relax_disp.relax_time(spectrum_id=id, time=Trelax) 
1091   
1092              # Set the relaxation dispersion CPMG frequencies. 
1093              ncyc = ncycs[i] 
1094              nu_cpmg = ncyc / Trelax 
1095              self.interpreter.relax_disp.cpmg_setup(spectrum_id=id, cpmg_frq=nu_cpmg) 
1096   
1097          # Prepare for R2eff reading. 
1098          self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_r2eff) 
1099          self.interpreter.pipe.switch(pipe_name=pipe_name_r2eff) 
1100   
1101          # Try reading the R2eff file. 
1102          self.interpreter.relax_disp.r2eff_read_spin(id="CPMG", file="test_w_error.out", dir=data_path, spin_id=':1@H', disp_point_col=1, data_col=2, error_col=3) 
1103   
1104          # Check the global data. 
1105          data = [ 
1106              ['cpmg_frqs', {'CPMG_20': 500.0, 'CPMG_10': 250.0, 'CPMG_40': 1000.0, 'CPMG_4': 100.0, 'CPMG_2': 50.0, 'CPMG_500': 12500.0, 'CPMG_8': 200.0}], 
1107              ['cpmg_frqs_list', list(array(ncycs)/Trelax) ], 
1108              ['dispersion_points', len(ncycs)], 
1109              ['exp_type', {'CPMG_20': 'SQ CPMG', 'CPMG_10': 'SQ CPMG', 'CPMG_40': 'SQ CPMG', 'CPMG_4': 'SQ CPMG', 'CPMG_2': 'SQ CPMG', 'CPMG_500': 'SQ CPMG', 'CPMG_8': 'SQ CPMG'}], 
1110              ['exp_type_list', ['SQ CPMG']], 
1111              ['spectrometer_frq', {'CPMG_20': 200000000.0, 'CPMG_10': 200000000.0, 'CPMG_40': 200000000.0, 'CPMG_4': 200000000.0, 'CPMG_2': 200000000.0, 'CPMG_500': 200000000.0, 'CPMG_8': 200000000.0}], 
1112              ['spectrometer_frq_count', 1], 
1113              ['spectrometer_frq_list', [sfrq]], 
1114              ['spectrum_ids', ['CPMG_2', 'CPMG_4', 'CPMG_8', 'CPMG_10', 'CPMG_20', 'CPMG_40', 'CPMG_500']] 
1115          ] 
1116          for name, value in data: 
1117              # Does it exist? 
1118              self.assert_(hasattr(cdp, name)) 
1119   
1120              # Check the object. 
1121              obj = getattr(cdp, name) 
1122              if not isinstance(data, dict): 
1123                  self.assertEqual(obj, value) 
1124   
1125              # Check the global dictionary data. 
1126              else: 
1127                  for id in ids: 
1128                      self.assertEqual(obj[id], value[id]) 
1129   
1130          # Check the spin data. 
1131          n_data = [ 
1132              [ 50.000000, 10.286255, 0.1], 
1133              [ 100.000000, 10.073083, 0.1], 
1134              [ 200.000000, 9.692746, 0.1], 
1135              [ 250.000000, 9.382441, 0.1], 
1136              [ 500.000000, 6.312396, 0.1], 
1137              [ 1000.000000, 3.957029, 0.1], 
1138              [ 12500.000000, 2.880420, 0.1] 
1139          ] 
1140          for disp_point, value, error in n_data: 
1141              id = 'sq_cpmg_200.00000000_0.000_%.3f' % disp_point 
1142              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff[id], value) 
1143              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff_err[id], error) 
1144   
1145          # Generate r20 key. 
1146          r20_key = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq) 
1147   
1148          ## Now prepare for MODEL calculation. 
1149          MODEL = "B14 full" 
1150   
1151          # Change pipe. 
1152          pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 
1153          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
1154          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
1155   
1156          # Then select model. 
1157          self.interpreter.relax_disp.select_model(model=MODEL) 
1158   
1159          # Store grid and minimisations results. 
1160          grid_results = [] 
1161          mini_results = [] 
1162          clust_results = [] 
1163   
1164          # The grid search size (the number of increments per dimension). 
1165          # If None, use the default values. 
1166          #GRID = None 
1167          GRID = 13 
1168          # Perform Grid Search. 
1169          if GRID: 
1170              # Set the R20 parameters in the default grid search using the minimum R2eff value. 
1171              # This speeds it up considerably. 
1172              self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
1173   
1174              # Then do grid search. 
1175              self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID, constraints=True, verbosity=1) 
1176   
1177              # If no Grid search, set the default values. 
1178          else: 
1179              for param in MODEL_PARAMS[MODEL]: 
1180                  self.interpreter.value.set(param=param, index=None) 
1181                  # Do a grid search, which will store the chi2 value. 
1182              self.interpreter.minimise.grid_search(lower=None, upper=None, inc=1, constraints=True, verbosity=1) 
1183   
1184          # Store result. 
1185          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1186              grid_results.append([spin.r2a[r20_key], spin.r2b[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
1187   
1188          ## Now do minimisation. 
1189          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
1190          set_func_tol = 1e-11 
1191          set_max_iter = 10000 
1192          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
1193   
1194          # Store result. 
1195          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1196              mini_results.append([spin.r2a[r20_key], spin.r2b[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
1197   
1198          print("\n# Now print before and after minimisation-\n") 
1199   
1200          # Print results. 
1201          for i in range(len(grid_results)): 
1202              g_r2a, g_r2b, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 
1203              m_r2a, m_r2b, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 
1204              print("GRID %s r2a=%2.4f r2b=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(g_spin_id, g_r2a, g_r2b, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 
1205              print("MIN  %s r2b=%2.4f r2b=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(m_spin_id, m_r2a, m_r2b, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 
1206   
1207          # Reference values from Baldwin.py. 
1208          # Exchange rate = k+ + k- (s-1) 
1209          kex = 1000. 
1210          # Fractional population of excited state k+/kex 
1211          pb = 0.01 
1212          # deltaOmega in ppm 
1213          dw_ppm = 2. 
1214          #relaxation rate of ground (s-1) 
1215          R2g = 2. 
1216          #relaxation rate of excited (s-1) 
1217          R2e = 100. 
1218   
1219          # Test the parameters which created the data. 
1220          # This is for the 1H spin. 
1221          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2a[r20_key], R2g, 3) 
1222          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2b[r20_key]/100, R2e/100, 3) 
1223   
1224          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].dw, dw_ppm, 6) 
1225          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].pA, 1-pb, 6) 
1226          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].kex/1000, kex/1000, 2) 
1227   
1228   
1229 -    def x_test_bmrb_sub_cpmg(self): 
1230          """U{Task #7858: <https://gna.org/task/?7858>} Make it possible to submit CPMG experiments for BMRB. 
1231          This uses CPMG data from: 
1232              - Webb H, Tynan-Connolly BM, Lee GM, Farrell D, O'Meara F, Soendergaard CR, Teilum K, Hewage C, McIntosh LP, Nielsen JE. 
1233                Remeasuring HEWL pK(a) values by NMR spectroscopy: methods, analysis, accuracy, and implications for theoretical pK(a) calculations. 
1234                (2011), Proteins: Struct, Funct, Bioinf 79(3):685-702, DOI 10.1002/prot.22886 
1235          """ 
1236   
1237          # Define path to data  
1238          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'HWebb_KTeilum_Proteins_Struct_Funct_Bioinf_2011' 
1239   
1240          # Read data. 
1241          self.interpreter.results.read(prev_data_path + sep + 'FT_-_CR72_-_min_-_128_-_free_spins') 
1242   
1243          # Set element 
1244          self.interpreter.spin.element(element='N', spin_id=':*@N', force=False) 
1245          #self.interpreter.spin.isotope(isotope='15N', spin_id=':*@N', force=False) 
1246          # Rename molecule from None to 'HEWL' 
1247          self.interpreter.molecule.name(mol_id=None, name='HEWL', force=True) 
1248          self.interpreter.molecule.type(mol_id='#HEWL', type='protein', force=False) 
1249   
1250          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1251              print(spin_id) 
1252              if resn == 'C': 
1253                  print(resi, resn) 
1254   
1255          # Select the thiol state of the system. 
1256          # 'all disulfide bound', 'all free', 'all other bound', 'disulfide and other bound', 'free and disulfide bound', 'free and other bound', 'free disulfide and other bound', 'not available', 'not present', 'not reported', 'unknown' 
1257          self.interpreter.bmrb.thiol_state(state='not reported') 
1258   
1259          # relax_data.temp_calibration(ri_id=None, method=None) 
1260   
1261          # Call display of bmrb. 
1262          self.interpreter.bmrb.display() 
1263   
1264   
1265 -    def test_bug_21081_disp_cluster_fail(self): 
1266          """U{Bug #21081<https://gna.org/bugs/?21081>} catch, the failure of a cluster analysis when spins are deselected.""" 
1267   
1268          # Clear the data store. 
1269          self.interpreter.reset() 
1270   
1271          # Load the state. 
1272          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'saved_states'+sep+'bug_21081_disp_cluster_fail.bz2' 
1273          self.interpreter.state.load(state, force=True) 
1274   
1275          # Model selection - to catch the failure. 
1276          self.interpreter.model_selection(method='AIC', modsel_pipe='final', bundle='relax_disp', pipes=['No Rex', 'CR72']) 
1277   
1278   
1279 -    def test_bug_21460_disp_cluster_fail(self): 
1280          """U{Bug #21460<https://gna.org/bugs/?21460>} catch, the failure due to a spectrometer frequency having no relaxation data.""" 
1281   
1282          # Clear the data store. 
1283          self.interpreter.reset() 
1284   
1285          # Load the state. 
1286          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'saved_states'+sep+'bug_21460_bad_fields.bz2' 
1287          self.interpreter.state.load(state, force=True) 
1288   
1289          # Execute the auto-analysis (fast). 
1290          relax_disp.Relax_disp.opt_func_tol = 1e-5 
1291          relax_disp.Relax_disp.opt_max_iterations = 1000 
1292          relax_disp.Relax_disp(pipe_name="origin - relax_disp (Thu Jan  2 13:46:44 2014)", pipe_bundle="relax_disp (Thu Jan  2 13:46:44 2014)", results_dir=self.tmpdir, models=['R2eff', 'No Rex', 'CR72', 'NS CPMG 2-site expanded'], grid_inc=3, mc_sim_num=5, modsel='AIC', pre_run_dir=None, insignificance=1.0, numeric_only=False, mc_sim_all_models=False, eliminate=True) 
1293   
1294   
1295 -    def test_bug_21344_sparse_time_spinlock_acquired_r1rho_fail_relax_disp(self): 
1296          """U{Bug #21665<https://gna.org/bugs/?21344>} catch, the failure of an analysis of a sparse acquired R1rho dataset with missing combinations of time and spin-lock field strengths using auto_analysis.""" 
1297   
1298          # Clear the data store. 
1299          self.interpreter.reset() 
1300   
1301          # Load the state. 
1302          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 
1303          self.interpreter.state.load(state, force=True) 
1304   
1305          # Execute the auto-analysis (fast). 
1306          relax_disp.Relax_disp.opt_func_tol = 1e-5 
1307          relax_disp.Relax_disp.opt_max_iterations = 1000 
1308          relax_disp.Relax_disp(pipe_name='base pipe', pipe_bundle='relax_disp', results_dir=self.tmpdir, models=['R2eff'], grid_inc=3, mc_sim_num=5, modsel='AIC', pre_run_dir=None, insignificance=1.0, numeric_only=False, mc_sim_all_models=False, eliminate=True) 
1309   
1310   
1311 -    def test_bug_21665_cpmg_two_fields_two_delaytimes_fail_calc(self): 
1312          """U{Bug #21665<https://gna.org/bugs/?21665>} catch, the failure due to a a CPMG analysis recorded at two fields at two delay times, using minimise.calculate().""" 
1313   
1314          # Clear the data store. 
1315          self.interpreter.reset() 
1316   
1317          # Load the state. 
1318          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21665.bz2' 
1319          self.interpreter.state.load(state, force=True) 
1320   
1321          # Run the calculation. 
1322          self.interpreter.minimise.calculate(verbosity=1) 
1323   
1324   
1325 -    def test_bug_21665_cpmg_two_fields_two_delaytimes_fail_relax_disp(self): 
1326          """U{Bug #21665<https://gna.org/bugs/?21665>} catch, the failure due to a a CPMG analysis recorded at two fields at two delay times using auto_analysis.""" 
1327   
1328          # Clear the data store. 
1329          self.interpreter.reset() 
1330   
1331          # Load the state. 
1332          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21665.bz2' 
1333          self.interpreter.state.load(state, force=True) 
1334   
1335          # Execute the auto-analysis (fast). 
1336          relax_disp.Relax_disp.opt_func_tol = 1e-5 
1337          relax_disp.Relax_disp.opt_max_iterations = 1000 
1338          relax_disp.Relax_disp(pipe_name="compare_128_FT_R2eff", pipe_bundle="cpmg_disp_sod1d90a", results_dir=self.tmpdir, models=['R2eff'], grid_inc=3, mc_sim_num=5, modsel='AIC', pre_run_dir=None, insignificance=1.0, numeric_only=False, mc_sim_all_models=False, eliminate=True) 
1339   
1340   
1341 -    def test_bug_21715_clustered_indexerror(self): 
1342          """Catch U{bug #21715<https://gna.org/bugs/?21715>}, the failure of a clustered auto-analysis due to an IndexError.""" 
1343   
1344          # Clear the data store. 
1345          self.interpreter.reset() 
1346   
1347          # Load the state. 
1348          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21715_clustered_indexerror'+sep+'state.bz2' 
1349          self.interpreter.state.load(state, force=True) 
1350   
1351          # Execute the auto-analysis (fast). 
1352          pre_run_dir = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21715_clustered_indexerror'+sep+'non_clustered' 
1353          relax_disp.Relax_disp.opt_func_tol = 1e-5 
1354          relax_disp.Relax_disp.opt_max_iterations = 1000 
1355          relax_disp.Relax_disp(pipe_name='origin - relax_disp (Sun Feb 23 19:36:51 2014)', pipe_bundle='relax_disp (Sun Feb 23 19:36:51 2014)', results_dir=self.tmpdir, models=['R2eff', 'No Rex'], grid_inc=11, mc_sim_num=2, modsel='AIC', pre_run_dir=pre_run_dir, insignificance=1.0, numeric_only=True, mc_sim_all_models=False, eliminate=True) 
1356   
1357   
1358 -    def test_bug_22146_unpacking_r2a_r2b_cluster_B14(self): 
1359          """Catch U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered B14 full analysis.""" 
1360   
1361          # Base data setup. 
1362          self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='B14_full', model_analyse = MODEL_B14_FULL) 
1363   
1364   
1365 -    def test_bug_22146_unpacking_r2a_r2b_cluster_CR72(self): 
1366          """Catch U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered CR72 full analysis.""" 
1367   
1368          # Base data setup. 
1369          self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='CR72_full', model_analyse = MODEL_CR72_FULL) 
1370   
1371   
1372 -    def test_bug_22146_unpacking_r2a_r2b_cluster_NS_3D(self): 
1373          """Catch U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered NS CPMG 2SITE 3D full analysis.""" 
1374   
1375          # Base data setup. 
1376          self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='ns_cpmg_2site_3d_full', model_analyse = MODEL_NS_CPMG_2SITE_3D_FULL) 
1377   
1378   
1379 -    def test_bug_22146_unpacking_r2a_r2b_cluster_NS_STAR(self): 
1380          """Catch U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered NS CPMG 2SITE STAR full analysis.""" 
1381   
1382          # Base data setup. 
1383          self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='ns_cpmg_2site_star_full', model_analyse = MODEL_NS_CPMG_2SITE_STAR_FULL, places = 4) 
1384   
1385   
1386 -    def test_bug_22477_grace_write_k_AB_mixed_analysis(self): 
1387          """Catch U{bug #22146<https://gna.org/bugs/?22477>}, the failure of issuing: grace.write(x_data_type='res_num', y_data_type=param) for a mixed CPMG analysis.""" 
1388   
1389          # Clear the data store. 
1390          self.interpreter.reset() 
1391   
1392          # Load the state. 
1393          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_22477_grace_write_k_AB_mixed_analysis'+sep+'bug_22477_results.bz2' 
1394          self.interpreter.state.load(state, force=True) 
1395   
1396          param = 'k_AB' 
1397   
1398          for spin, spin_id in spin_loop(return_id=True, skip_desel=True): 
1399              print(spin_id, spin.params) 
1400              if param in spin.params: 
1401                  print(spin_id, spin.k_AB, spin.k_AB_err) 
1402   
1403          # Perform write. 
1404          self.interpreter.grace.write(x_data_type='res_num', y_data_type=param, file='%s.agr'%param, dir=self.tmpdir, force=True) 
1405   
1406   
1407          # Test the header of the value.write  parameter r2. 
1408          param = 'r2' 
1409          self.interpreter.value.write(param=param, file='%s.out'%param, dir=self.tmpdir, force=True) 
1410   
1411          file = open(self.tmpdir+sep+'%s.out'%param) 
1412          lines = file.readlines() 
1413          file.close() 
1414   
1415          for i, line in enumerate(lines): 
1416              # Make the string test 
1417              line_split = line.split() 
1418              print(line_split) 
1419   
1420              if len(line_split) > 1: 
1421                  # Break at parameter header. 
1422                  if line_split[0] == "#" and line_split[1] == 'mol_name': 
1423                      nr_split_header = len(line_split) 
1424                      nr_split_header_i = i 
1425                      break 
1426   
1427          # Call the line after. 
1428          line_split_val = lines[nr_split_header_i + 1].split() 
1429          print(line_split_val) 
1430   
1431          # Assert that the number of columns is equal, plus 1 for "#". 
1432          self.assertEqual(nr_split_header, len(line_split_val) + 1) 
1433   
1434          # Test the header of the value.write for parameter r2eff. 
1435          param = 'r2eff' 
1436          self.interpreter.value.write(param=param, file='%s.out'%param, dir=self.tmpdir, force=True) 
1437   
1438          file = open(self.tmpdir+sep+'%s.out'%param) 
1439          lines = file.readlines() 
1440          file.close() 
1441   
1442          for i, line in enumerate(lines): 
1443              # Make the string test 
1444              line_split = line.split() 
1445              print(line_split) 
1446   
1447              if len(line_split) > 1: 
1448                  # Break at parameter header. 
1449                  if line_split[0] == "#" and line_split[1] == 'mol_name': 
1450                      nr_split_header = len(line_split) 
1451                      nr_split_header_i = i 
1452                      break 
1453   
1454          # Call the line after. 
1455          line_split_val = lines[nr_split_header_i + 1].split() 
1456          print(line_split_val) 
1457   
1458          # Assert that the number of columns is equal, plus 1 for "#". 
1459          self.assertEqual(nr_split_header, len(line_split_val) + 1) 
1460   
1461   
1462 -    def test_bug_9999_slow_r1rho_r2eff_error_with_mc(self): 
1463          """Catch U{bug #9999<https://gna.org/bugs/?9999>}, The slow optimisation of R1rho R2eff error estimation with Monte Carlo simulations.""" 
1464   
1465          # Define path to data  
1466          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' +sep+ "check_graphs" +sep+ "mc_2000"  +sep+ "R2eff" 
1467   
1468          # Read data. 
1469          self.interpreter.results.read(prev_data_path + sep + 'results')         
1470   
1471          # Now count number 
1472          graph_nr = 1 
1473          for exp_type, frq, offset, point in loop_exp_frq_offset_point(return_indices=False): 
1474              print("\nGraph nr %i" % graph_nr) 
1475              for time in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point): 
1476                  print(exp_type, frq, offset, point, time) 
1477              graph_nr += 1 
1478   
1479          ## Possibly do an error analysis. 
1480   
1481          # Check if intensity errors have already been calculated by the user. 
1482          precalc = True 
1483          for spin in spin_loop(skip_desel=True): 
1484              # No structure. 
1485              if not hasattr(spin, 'peak_intensity_err'): 
1486                  precalc = False 
1487                  break 
1488   
1489              # Determine if a spectrum ID is missing from the list. 
1490              for id in cdp.spectrum_ids: 
1491                  if id not in spin.peak_intensity_err: 
1492                      precalc = False 
1493                      break 
1494   
1495          # Skip. 
1496          if precalc: 
1497              print("Skipping the error analysis as it has already been performed.") 
1498   
1499          else: 
1500              # Loop over the spectrometer frequencies. 
1501              for frq in loop_frq(): 
1502                  # Generate a list of spectrum IDs matching the frequency. 
1503                  ids = [] 
1504                  for id in cdp.spectrum_ids: 
1505                      # Check that the spectrometer frequency matches. 
1506                      match_frq = True 
1507                      if frq != None and cdp.spectrometer_frq[id] != frq: 
1508                          match_frq = False 
1509   
1510                      # Add the ID. 
1511                      if match_frq: 
1512                          ids.append(id) 
1513   
1514                  # Run the error analysis on the subset. 
1515                  self.interpreter.spectrum.error_analysis(subset=ids) 
1516   
1517          print("has_exponential_exp_type:", has_exponential_exp_type()) 
1518   
1519          model = 'R2eff' 
1520          self.interpreter.relax_disp.select_model(model) 
1521   
1522          for spin, spin_id in spin_loop(return_id=True, skip_desel=True): 
1523              #delattr(spin, 'r2eff') 
1524              #delattr(spin, 'r2eff_err') 
1525              #delattr(spin, 'i0') 
1526              #delattr(spin, 'i0_err') 
1527              setattr(spin, 'r2eff', {}) 
1528              setattr(spin, 'r2eff_err', {}) 
1529              setattr(spin, 'i0', {}) 
1530              setattr(spin, 'i0_err', {}) 
1531   
1532          # Do Grid Search 
1533          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=21, constraints=True, verbosity=1) 
1534   
1535          # Start dic. 
1536          my_dic = {} 
1537   
1538          # Define counter for maximum elements in the numpy array list 
1539          NE = 0 
1540          NS = 1 
1541          NM = 0 
1542          NO = 0 
1543          ND = 0 
1544          NT = 0 
1545   
1546          for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
1547              # Save to counter. 
1548              if ei > NE: 
1549                  NE = ei 
1550              if mi > NM: 
1551                  NM = mi 
1552              if oi > NO: 
1553                  NO = oi 
1554              if di > ND: 
1555                 ND = di 
1556   
1557              for time, ti in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point, return_indices=True): 
1558                  # Save to counter. 
1559                  if ti > NT: 
1560                      NT = ti 
1561   
1562          # Add 1 to counter, since index start from 0. 
1563          NE = NE + 1 
1564          NM = NM + 1  
1565          NO = NO + 1 
1566          ND = ND + 1 
1567          NT = NT + 1 
1568   
1569          # Make data array. 
1570          values_arr = zeros([NE, NS, NM, NO, ND, NT]) 
1571          errors_arr = zeros([NE, NS, NM, NO, ND, NT]) 
1572          times_arr = zeros([NE, NS, NM, NO, ND, NT]) 
1573          struct_arr = zeros([NE, NS, NM, NO, ND, NT]) 
1574          param_key_list = [] 
1575   
1576   
1577          # Loop over each spectrometer frequency and dispersion point. 
1578          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1579              # Add key to dic. 
1580              my_dic[spin_id] = {} 
1581   
1582              # Generate spin string. 
1583              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
1584   
1585              # Loop over the parameters. 
1586              #print("Grid optimised parameters for spin: %s" % (spin_string)) 
1587   
1588              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
1589                  # Generate the param_key. 
1590                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
1591   
1592                  # Append key. 
1593                  param_key_list.append(param_key) 
1594   
1595                  # Add key to dic. 
1596                  my_dic[spin_id][param_key] = {} 
1597   
1598                  # Get the value. 
1599                  R2eff_value = getattr(cur_spin, 'r2eff')[param_key] 
1600                  i0_value = getattr(cur_spin, 'i0')[param_key] 
1601   
1602                  # Save to dic. 
1603                  my_dic[spin_id][param_key]['R2eff_value_grid'] = R2eff_value 
1604                  my_dic[spin_id][param_key]['i0_value_grid'] = i0_value 
1605   
1606                  ## Now try do a line of best fit by least squares. 
1607                  # The peak intensities, errors and times. 
1608                  values = [] 
1609                  errors = [] 
1610                  times = [] 
1611                  for time, ti in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point, return_indices=True): 
1612                      value = average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, sim_index=None) 
1613                      values.append(value) 
1614   
1615                      error = average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, error=True) 
1616                      errors.append(error) 
1617                      times.append(time) 
1618   
1619                      # Save to numpy arrays. 
1620                      values_arr[ei, 0, mi, oi, di, ti] = value 
1621                      errors_arr[ei, 0, mi, oi, di, ti] = error 
1622                      times_arr[ei, 0, mi, oi, di, ti] = time 
1623                      struct_arr[ei, 0, mi, oi, di, ti] = 1.0 
1624   
1625                  # y= A exp(x * k) 
1626                  # w[i] = ln(y[i]) 
1627                  # int[i] = i0 * exp( - times[i] * r2eff); 
1628                  w = log(array(values)) 
1629                  x = - array(times) 
1630                  n = len(times) 
1631   
1632                  b = (sum(x*w) - 1./n * sum(x) * sum(w) ) / ( sum(x**2) - 1./n * (sum(x))**2 ) 
1633                  a = 1./n * sum(w) - b * 1./n * sum(x) 
1634                  R2eff_est = b 
1635                  i0_est = exp(a) 
1636   
1637                  my_dic[spin_id][param_key]['R2eff_est'] = R2eff_est 
1638                  my_dic[spin_id][param_key]['i0_est'] = i0_est 
1639   
1640                  # Print value. 
1641                  #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:", 'R2eff', "Value : Estimated:", R2eff_value, R2eff_est)) 
1642                  #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:", 'i0', "Value: Estimated:", i0_value, i0_est)) 
1643   
1644   
1645          # Do minimisation. 
1646          set_func_tol = 1e-25 
1647          set_max_iter = int(1e7) 
1648          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
1649   
1650          # Loop over each spectrometer frequency and dispersion point. 
1651          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1652              # Generate spin string. 
1653              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
1654   
1655              # Loop over the parameters. 
1656              print("Optimised parameters for spin: %s" % (spin_string)) 
1657   
1658              for exp_type, frq, offset, point in loop_exp_frq_offset_point(): 
1659                  # Generate the param_key. 
1660                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
1661   
1662                  # Get the value. 
1663                  R2eff_value = getattr(cur_spin, 'r2eff')[param_key] 
1664                  i0_value = getattr(cur_spin, 'i0')[param_key] 
1665   
1666                  # Extract from dic. 
1667                  R2eff_value_grid = my_dic[spin_id][param_key]['R2eff_value_grid'] 
1668                  i0_value_grid = my_dic[spin_id][param_key]['i0_value_grid'] 
1669                  R2eff_est = my_dic[spin_id][param_key]['R2eff_est'] 
1670                  i0_est = my_dic[spin_id][param_key]['i0_est'] 
1671   
1672                  # Print value. 
1673                  #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:", 'R2eff', "Value : Estimated:", R2eff_value, R2eff_est)) 
1674                  #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:", 'i0', "Value: Estimated:", i0_value, i0_est)) 
1675   
1676                  print("%-10s %-6s %-6s %3.1f : %3.1f: %3.1f" % ("Parameter:", 'R2eff', "Grid : Min : Estimated:", R2eff_value_grid, R2eff_value, R2eff_est)) 
1677                  print("%-10s %-6s %-6s %3.1f : %3.1f: %3.1f" % ("Parameter:", 'i0', "Grid : Min : Estimated:", i0_value_grid, i0_value, i0_est)) 
1678   
1679          print(NE, NS, NM, NO, ND, NT) 
1680          for param_key in param_key_list: 
1681              print("        '%s'," % param_key) 
1682          print(values_arr.shape) 
1683   
1684          # Save arrays to profiling. 
1685          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'curve_fitting'+sep+'profiling'+sep 
1686          #save(data_path + "values_arr", values_arr) 
1687          #save(data_path + "errors_arr", errors_arr) 
1688          #save(data_path + "times_arr", times_arr) 
1689          #save(data_path + "struct_arr", struct_arr) 
1690   
1691   
1692 -    def test_bug_atul_srivastava(self): 
1693          """Test data from Atul Srivastava.  This is a bug missing raising a Relax Error, since the setup points to a situation where the data 
1694          shows it is exponential fitting, but only one time point is added per file. 
1695   
1696          This follows: U{Thread <http://thread.gmane.org/gmane.science.nmr.relax.user/1718>}: 
1697          This follows: U{Thread <http://thread.gmane.org/gmane.science.nmr.relax.user/1735>}: 
1698          This follows: U{Thread <http://thread.gmane.org/gmane.science.nmr.relax.user/1735/focus=1736>}: 
1699   
1700          """ 
1701   
1702          # Data path. 
1703          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_Atul_Srivastava' 
1704          file = data_path + sep + 'bug_script.py' 
1705   
1706          # Run script. 
1707          self.interpreter.script(file=file, dir=None) 
1708   
1709          # The grid search size (the number of increments per dimension). 
1710          GRID_INC = 11 
1711   
1712          # Check-data. 
1713          ################# 
1714   
1715          # Loop over spins, to see current setup. 
1716          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1717              print(mol_name, resi, resn, spin_id) 
1718   
1719          # Loop over setup. 
1720          for id in cdp.exp_type: 
1721              print(id, cdp.exp_type[id], cdp.spectrometer_frq[id], cdp.spin_lock_offset[id], cdp.spin_lock_nu1[id]) 
1722   
1723   
1724          # Manual minimisation. 
1725          ################# 
1726          if True: 
1727              # Set the model. 
1728              self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
1729   
1730              # Check if intensity errors have already been calculated. 
1731              check_intensity_errors() 
1732   
1733              # Calculate the R2eff values for the fixed relaxation time period data types. 
1734              if cdp.model_type == MODEL_R2EFF and not has_exponential_exp_type(): 
1735                  self.interpreter.minimise.calculate() 
1736   
1737              # Optimise the model. 
1738              else: 
1739                  constraints = False 
1740                  min_algor = 'Newton' 
1741                  self.assertRaises(RelaxError, self.interpreter.minimise.grid_search, inc=GRID_INC) 
1742                  self.assertRaises(RelaxError, self.interpreter.minimise.execute, min_algor=min_algor, constraints=constraints) 
1743   
1744          # Inspect. 
1745          if False: 
1746              # Loop over attributes. 
1747              par_attr_list = ['r2eff', 'i0'] 
1748   
1749              # Collect the estimation data. 
1750              my_dic = {} 
1751              param_key_list = [] 
1752              est_keys = [] 
1753              est_key = 'grid' 
1754              est_keys.append(est_key) 
1755              spin_id_list = [] 
1756   
1757              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1758                  # Add key to dic. 
1759                  my_dic[spin_id] = {} 
1760   
1761                  # Add key for estimate. 
1762                  my_dic[spin_id][est_key] = {} 
1763   
1764                  # Add spin key to list. 
1765                  spin_id_list.append(spin_id) 
1766   
1767                  # Generate spin string. 
1768                  spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
1769   
1770                  for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
1771                      # Generate the param_key. 
1772                      param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
1773                      #param_key = generate_r20_key(exp_type=exp_type, frq=frq) 
1774   
1775                      # Append key. 
1776                      param_key_list.append(param_key) 
1777   
1778                      # Add key to dic. 
1779                      my_dic[spin_id][est_key][param_key] = {} 
1780   
1781                      # Get the value. 
1782                      # Loop over err attributes. 
1783                      for par_attr in par_attr_list: 
1784                          if hasattr(cur_spin, par_attr): 
1785                              get_par_attr = getattr(cur_spin, par_attr)[param_key] 
1786                          else: 
1787                              get_par_attr = 0.0 
1788   
1789                          # Save to dic. 
1790                          my_dic[spin_id][est_key][param_key][par_attr] = get_par_attr 
1791   
1792                      # Check number of values. 
1793                      values = [] 
1794                      errors = [] 
1795                      times = [] 
1796                      for time, ti in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point, return_indices=True): 
1797                          value = average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, sim_index=None) 
1798                          values.append(value) 
1799   
1800                          error = average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, error=True) 
1801                          errors.append(error) 
1802                          times.append(time) 
1803   
1804                      # Save to dic. 
1805                      my_dic[spin_id][est_key][param_key]['values'] = values 
1806                      my_dic[spin_id][est_key][param_key]['errors'] = errors 
1807                      my_dic[spin_id][est_key][param_key]['times'] = times 
1808   
1809          # Analysis variables. 
1810          ##################### 
1811   
1812          # The dispersion models. 
1813          MODELS = ['R2eff', 'No Rex'] 
1814   
1815          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
1816          MC_NUM = 10 
1817   
1818          # A flag which if True will activate Monte Carlo simulations for all models.  Note this will hugely increase the computation time. 
1819          MC_SIM_ALL_MODELS = False 
1820   
1821          # The results directory. 
1822          RESULTS_DIR = ds.tmpdir 
1823   
1824          # The directory of results of an earlier analysis without clustering. 
1825          PRE_RUN_DIR = None 
1826   
1827          # The model selection technique to use. 
1828          MODSEL = 'AIC' 
1829   
1830          # The flag for only using numeric models in the final model selection. 
1831          NUMERIC_ONLY = False 
1832   
1833          # The R1rho value in rad/s by which to judge insignificance.  If the maximum difference between two points on all dispersion curves for a spin is less than this value, that spin will be deselected. 
1834          INSIGNIFICANCE = 1.0 
1835   
1836          # Auto-analysis execution. 
1837          self.assertRaises(RelaxError, relax_disp.Relax_disp, pipe_name='relax_disp', results_dir=RESULTS_DIR, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL, insignificance=INSIGNIFICANCE, numeric_only=NUMERIC_ONLY) 
1838   
1839   
1840 -    def test_bug_negative_intensities_cpmg(self): 
1841          """Test data, where peak intensities are negative in CPMG 
1842   
1843          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
1844          """ 
1845   
1846          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'KTeilum_FMPoulsen_MAkke_2006'+sep+'bug_neg_int_acbp_cpmg_disp_048MGuHCl_40C_041223' 
1847   
1848          # Create the spins 
1849          self.interpreter.spectrum.read_spins(file="peaks_list_max_standard.ser", dir=data_path) 
1850   
1851          # Name the isotope for field strength scaling. 
1852          self.interpreter.spin.isotope(isotope='15N') 
1853   
1854          # Read the spectrum from NMRSeriesTab file. The "auto" will generate spectrum name of form: Z_A{i} 
1855          self.interpreter.spectrum.read_intensities(file="peaks_list_max_standard.ser", dir=data_path, spectrum_id='auto', int_method='height') 
1856   
1857          # Loop over the spectra settings. 
1858          ncycfile=open(data_path + sep + 'ncyc.txt', 'r') 
1859   
1860          # Make empty ncyclist 
1861          ncyclist = [] 
1862   
1863          i = 0 
1864          for line in ncycfile: 
1865              ncyc = line.split()[0] 
1866              time_T2 = float(line.split()[1]) 
1867              vcpmg = line.split()[2] 
1868              set_sfrq = float(line.split()[3]) 
1869              rmsd_err = float(line.split()[4]) 
1870   
1871              # Test if spectrum is a reference 
1872              if float(vcpmg) == 0.0: 
1873                  vcpmg = None 
1874              else: 
1875                  vcpmg = round(float(vcpmg), 3) 
1876   
1877              # Add ncyc to list 
1878              ncyclist.append(int(ncyc)) 
1879   
1880              # Set the current spectrum id 
1881              current_id = "Z_A%s"%(i) 
1882   
1883              # Set the current experiment type. 
1884              self.interpreter.relax_disp.exp_type(spectrum_id=current_id, exp_type='SQ CPMG') 
1885   
1886              # Set the peak intensity errors, as defined as the baseplane RMSD. 
1887              self.interpreter.spectrum.baseplane_rmsd(error=rmsd_err, spectrum_id=current_id) 
1888   
1889              # Set the NMR field strength of the spectrum. 
1890              self.interpreter.spectrometer.frequency(id=current_id, frq=set_sfrq, units='MHz') 
1891   
1892              # Relaxation dispersion CPMG constant time delay T (in s). 
1893              self.interpreter.relax_disp.relax_time(spectrum_id=current_id, time=time_T2) 
1894   
1895              # Set the relaxation dispersion CPMG frequencies. 
1896              self.interpreter.relax_disp.cpmg_setup(spectrum_id=current_id, cpmg_frq=vcpmg) 
1897   
1898              i += 1 
1899   
1900          # Specify the duplicated spectra. 
1901          self.interpreter.spectrum.replicated(spectrum_ids=['Z_A1', 'Z_A15']) 
1902   
1903          # Delete replicate spectrum 
1904          #self.interpreter.spectrum.delete('Z_A15') 
1905   
1906          MODELS = [MODEL_R2EFF, MODEL_NOREX] 
1907          GRID_INC = 5; MC_NUM = 3; MODSEL = 'AIC' 
1908   
1909          results_dir = ds.tmpdir 
1910   
1911          # Execute 
1912          relax_disp.Relax_disp(pipe_name='relax_disp', results_dir=results_dir, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL) 
1913   
1914          # Check spin less R2eff points. 
1915          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=False): 
1916              # Assert that spin 4, has one less R2eff point, since one of the intensities are negative. 
1917              if spin_id == ':4@N': 
1918                  self.assertEqual(len(cur_spin.r2eff), 14) 
1919              else: 
1920                  self.assertEqual(len(cur_spin.r2eff), 15) 
1921   
1922   
1923 -    def test_check_missing_r1(self): 
1924          """Test of the check_missing_r1() function.""" 
1925   
1926          # Set up some spins. 
1927          self.setup_missing_r1_spins() 
1928   
1929          # Set variables. 
1930          exp_type = 'R1rho' 
1931          frq = 800.1 * 1E6 
1932   
1933          spectrum_id='test' 
1934   
1935          # Set an experiment type to the pipe. 
1936          self.interpreter.relax_disp.exp_type(spectrum_id=spectrum_id, exp_type=exp_type) 
1937   
1938          # Set a frequency to loop through. 
1939          self.interpreter.spectrometer.frequency(id=spectrum_id, frq=frq, units='Hz') 
1940   
1941          # Check R1 for DPL94. 
1942          check_missing_r1_return = check_missing_r1(model=MODEL_DPL94) 
1943          self.assertEqual(check_missing_r1_return, True) 
1944   
1945          # Check R1 for R2eff. 
1946          check_missing_r1_return = check_missing_r1(model=MODEL_R2EFF) 
1947          self.assertEqual(check_missing_r1_return, False) 
1948   
1949          # The path to the data files. 
1950          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' 
1951   
1952          # Now load some R1 data. 
1953          self.interpreter.relax_data.read(ri_id='R1', ri_type='R1', frq=cdp.spectrometer_frq_list[0], file='R1_fitted_values.txt', dir=data_path, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5, data_col=6, error_col=7) 
1954   
1955          # Check R1. 
1956          check_missing_r1_return = check_missing_r1(model=MODEL_DPL94) 
1957          self.assertEqual(check_missing_r1_return, False) 
1958   
1959   
1960 -    def test_cpmg_synthetic_b14_to_ns3d_cluster(self): 
1961          """Test synthetic cpmg data.  Created with B14, analysed with NS CPMG 2site 3D, for clustered analysis. 
1962   
1963          This is part of: U{Task #7807 <https://gna.org/task/index.php?7807>}: Speed-up of dispersion models for Clustered analysis. 
1964   
1965          This script will produce synthetic CPMG R2eff values according to the selected model, and the fit the selected model. 
1966          """ 
1967   
1968          # Reset. 
1969          #self.interpreter.reset() 
1970   
1971          ## Set Experiments. 
1972          model_create = 'B14' 
1973          #model_create = 'NS CPMG 2-site expanded' 
1974          model_analyse = 'NS CPMG 2-site 3D' 
1975   
1976          # Exp 1 
1977          sfrq_1 = 599.8908617*1E6 
1978          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
1979          time_T2_1 = 0.06 
1980          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
1981          #r2eff_errs_1 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
1982          r2eff_errs_1 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
1983          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_errs_1] 
1984   
1985          sfrq_2 = 499.8908617*1E6 
1986          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
1987          time_T2_2 = 0.05 
1988          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
1989          #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
1990          r2eff_errs_2 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
1991          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_errs_2] 
1992   
1993          # Collect all exps 
1994          exps = [exp_1, exp_2] 
1995   
1996          spins = [ 
1997              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:11.5}, 'r2a': {r20_key_1:10., r20_key_2:11.5}, 'r2b': {r20_key_1:10., r20_key_2:11.5}, 'kex': 1000., 'pA': 0.95, 'dw': 2.} ], 
1998              ['Ala', 2, 'N', {'r2': {r20_key_1:13., r20_key_2:14.5}, 'r2a': {r20_key_1:13., r20_key_2:14.5}, 'r2b': {r20_key_1:13., r20_key_2:14.5}, 'kex': 1000., 'pA': 0.95, 'dw': 1.} ] 
1999              ] 
2000   
2001          # Collect the data to be used. 
2002          ds.data = [model_create, model_analyse, spins, exps] 
2003   
2004          # The tmp directory. None is the local directory. 
2005          ds.tmpdir = ds.tmpdir 
2006   
2007          # The results directory. None is the local directory. 
2008          #ds.resdir = None 
2009          ds.resdir = ds.tmpdir 
2010   
2011          # Do r20_from_min_r2eff ?. 
2012          ds.r20_from_min_r2eff = True 
2013   
2014          # Remove insignificant level. 
2015          ds.insignificance = 0.0 
2016   
2017          # The grid search size (the number of increments per dimension). 
2018          ds.GRID_INC = None 
2019   
2020          # The do clustering. 
2021          ds.do_cluster = True 
2022   
2023          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2024          # The default value is 1e-25. 
2025          ds.set_func_tol = 1e-1 
2026   
2027          # The maximum number of iterations. 
2028          # The default value is 1e7. 
2029          ds.set_max_iter = 1000 
2030   
2031          # The verbosity level. 
2032          ds.verbosity = 1 
2033   
2034          # The rel_change WARNING level. 
2035          ds.rel_change = 0.05 
2036   
2037          # The plot_curves. 
2038          ds.plot_curves = False 
2039   
2040          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2041          ds.sherekhan_input = False 
2042   
2043          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2044          ds.opendx = False 
2045   
2046          # The set r2eff err. 
2047          ds.r2eff_err = 0.1 
2048   
2049          # The print result info. 
2050          ds.print_res = True 
2051   
2052          # Execute the script. 
2053          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2054   
2055          cur_spins = ds.data[2] 
2056          # Compare results. 
2057          for i in range(len(cur_spins)): 
2058              res_name, res_num, spin_name, params = cur_spins[i] 
2059              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2060              cur_spin = return_spin(cur_spin_id) 
2061   
2062              grid_params = ds.grid_results[i][3] 
2063   
2064              # Extract the clust results. 
2065              min_params = ds.clust_results[i][3] 
2066              # Now read the parameters. 
2067              print("For spin: '%s'"%cur_spin_id) 
2068              for mo_param in cur_spin.params: 
2069                  # The R2 is a dictionary, depending on spectrometer frequency. 
2070                  if isinstance(getattr(cur_spin, mo_param), dict): 
2071                      grid_r2 = grid_params[mo_param] 
2072                      min_r2 = min_params[mo_param] 
2073                      set_r2 = params[mo_param] 
2074                      for key, val in list(set_r2.items()): 
2075                          grid_r2_frq = grid_r2[key] 
2076                          min_r2_frq = min_r2[key] 
2077                          set_r2_frq = set_r2[key] 
2078                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2079                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2080                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2081                          if rel_change > ds.rel_change: 
2082                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2083                              print("###################################") 
2084   
2085                          ## Make test on R2. 
2086                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 1) 
2087                  else: 
2088                      grid_val = grid_params[mo_param] 
2089                      min_val = min_params[mo_param] 
2090                      set_val = params[mo_param] 
2091                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2092                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2093                      if rel_change > ds.rel_change: 
2094                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2095                          print("###################################") 
2096   
2097                      ## Make test on parameters. 
2098                      if mo_param == 'dw': 
2099                          self.assertAlmostEqual(set_val/10, min_val/10, 1) 
2100                      elif mo_param == 'kex': 
2101                          self.assertAlmostEqual(set_val/1000, min_val/1000, 1) 
2102                      elif mo_param == 'pA': 
2103                          self.assertAlmostEqual(set_val, min_val, 2) 
2104   
2105   
2106 -    def test_cpmg_synthetic_b14_to_ns_star_cluster(self): 
2107          """Test synthetic cpmg data.  Created with B14, analysed with NS CPMG 2site STAR, for clustered analysis. 
2108   
2109          This is part of: U{Task #7807 <https://gna.org/task/index.php?7807>}: Speed-up of dispersion models for Clustered analysis. 
2110   
2111          This script will produce synthetic CPMG R2eff values according to the selected model, and the fit the selected model. 
2112          """ 
2113   
2114          # Reset. 
2115          #self.interpreter.reset() 
2116   
2117          ## Set Experiments. 
2118          model_create = 'B14' 
2119          #model_create = 'NS CPMG 2-site expanded' 
2120          model_analyse = 'NS CPMG 2-site star' 
2121   
2122          # Exp 1 
2123          sfrq_1 = 599.8908617*1E6 
2124          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2125          time_T2_1 = 0.06 
2126          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2127          #r2eff_errs_1 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2128          r2eff_errs_1 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2129          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_errs_1] 
2130   
2131          sfrq_2 = 499.8908617*1E6 
2132          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2133          time_T2_2 = 0.05 
2134          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2135          #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2136          r2eff_errs_2 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2137          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_errs_2] 
2138   
2139          # Collect all exps 
2140          exps = [exp_1, exp_2] 
2141   
2142          spins = [ 
2143              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:11.5}, 'r2a': {r20_key_1:10., r20_key_2:11.5}, 'r2b': {r20_key_1:10., r20_key_2:11.5}, 'kex': 1000., 'pA': 0.95, 'dw': 2.} ], 
2144              ['Ala', 2, 'N', {'r2': {r20_key_1:13., r20_key_2:14.5}, 'r2a': {r20_key_1:13., r20_key_2:14.5}, 'r2b': {r20_key_1:13., r20_key_2:14.5}, 'kex': 1000., 'pA': 0.95, 'dw': 1.} ] 
2145              ] 
2146   
2147          # Collect the data to be used. 
2148          ds.data = [model_create, model_analyse, spins, exps] 
2149   
2150          # The tmp directory. None is the local directory. 
2151          ds.tmpdir = ds.tmpdir 
2152   
2153          # The results directory. None is the local directory. 
2154          #ds.resdir = None 
2155          ds.resdir = ds.tmpdir 
2156   
2157          # Do r20_from_min_r2eff ?. 
2158          ds.r20_from_min_r2eff = True 
2159   
2160          # Remove insignificant level. 
2161          ds.insignificance = 0.0 
2162   
2163          # The grid search size (the number of increments per dimension). 
2164          ds.GRID_INC = None 
2165   
2166          # The do clustering. 
2167          ds.do_cluster = True 
2168   
2169          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2170          # The default value is 1e-25. 
2171          ds.set_func_tol = 1e-1 
2172   
2173          # The maximum number of iterations. 
2174          # The default value is 1e7. 
2175          ds.set_max_iter = 1000 
2176   
2177          # The verbosity level. 
2178          ds.verbosity = 1 
2179   
2180          # The rel_change WARNING level. 
2181          ds.rel_change = 0.05 
2182   
2183          # The plot_curves. 
2184          ds.plot_curves = False 
2185   
2186          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2187          ds.sherekhan_input = False 
2188   
2189          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2190          ds.opendx = False 
2191   
2192          # The set r2eff err. 
2193          ds.r2eff_err = 0.1 
2194   
2195          # The print result info. 
2196          ds.print_res = True 
2197   
2198          # Execute the script. 
2199          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2200   
2201          cur_spins = ds.data[2] 
2202          # Compare results. 
2203          for i in range(len(cur_spins)): 
2204              res_name, res_num, spin_name, params = cur_spins[i] 
2205              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2206              cur_spin = return_spin(cur_spin_id) 
2207   
2208              grid_params = ds.grid_results[i][3] 
2209   
2210              # Extract the clust results. 
2211              min_params = ds.clust_results[i][3] 
2212              # Now read the parameters. 
2213              print("For spin: '%s'"%cur_spin_id) 
2214              for mo_param in cur_spin.params: 
2215                  # The R2 is a dictionary, depending on spectrometer frequency. 
2216                  if isinstance(getattr(cur_spin, mo_param), dict): 
2217                      grid_r2 = grid_params[mo_param] 
2218                      min_r2 = min_params[mo_param] 
2219                      set_r2 = params[mo_param] 
2220                      for key, val in list(set_r2.items()): 
2221                          grid_r2_frq = grid_r2[key] 
2222                          min_r2_frq = min_r2[key] 
2223                          set_r2_frq = set_r2[key] 
2224                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2225                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2226                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2227                          if rel_change > ds.rel_change: 
2228                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2229                              print("###################################") 
2230   
2231                          ## Make test on R2. 
2232                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 1) 
2233                  else: 
2234                      grid_val = grid_params[mo_param] 
2235                      min_val = min_params[mo_param] 
2236                      set_val = params[mo_param] 
2237                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2238                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2239                      if rel_change > ds.rel_change: 
2240                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2241                          print("###################################") 
2242   
2243                      ## Make test on parameters. 
2244                      if mo_param == 'dw': 
2245                          self.assertAlmostEqual(set_val/10, min_val/10, 1) 
2246                      elif mo_param == 'kex': 
2247                          self.assertAlmostEqual(set_val/1000, min_val/1000, 1) 
2248                      elif mo_param == 'pA': 
2249                          self.assertAlmostEqual(set_val, min_val, 2) 
2250   
2251   
2252 -    def test_cpmg_synthetic_ns3d_to_cr72(self): 
2253          """Test synthetic cpmg data. 
2254   
2255          This script will produce synthetic CPMG R2eff values according to the NS CPMG 2-site 3D model, and the fit the data with CR72. 
2256          """ 
2257   
2258          # Reset. 
2259          #self.interpreter.reset() 
2260   
2261          ## Set Experiments. 
2262          model_create = 'NS CPMG 2-site 3D' 
2263          #model_create = 'NS CPMG 2-site expanded' 
2264          model_analyse = 'CR72' 
2265          # Exp 1 
2266          sfrq_1 = 599.8908617*1E6 
2267          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2268          time_T2_1 = 0.06 
2269          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2270          r2eff_err_1 = [0, 0, 0, 0, 0, 0, 0, 0] 
2271          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_err_1] 
2272   
2273          sfrq_2 = 499.8908617*1E6 
2274          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2275          time_T2_2 = 0.05 
2276          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2277          r2eff_err_2 = [0, 0, 0, 0, 0, 0, 0, 0] 
2278          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_err_2] 
2279   
2280          # Collect all exps 
2281          exps = [exp_1, exp_2] 
2282   
2283          spins = [ 
2284              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:10.}, 'r2a': {r20_key_1:10., r20_key_2:10.}, 'r2b': {r20_key_1:10., r20_key_2:10.}, 'kex': 1000., 'pA': 0.99, 'dw': 2.} ] 
2285              ] 
2286   
2287          # Collect the data to be used. 
2288          ds.data = [model_create, model_analyse, spins, exps] 
2289   
2290          # The tmp directory. None is the local directory. 
2291          ds.tmpdir = ds.tmpdir 
2292   
2293          # The results directory. None is the local directory. 
2294          #ds.resdir = None 
2295          ds.resdir = ds.tmpdir 
2296   
2297          # Do r20_from_min_r2eff ?. 
2298          ds.r20_from_min_r2eff = True 
2299   
2300          # Remove insignificant level. 
2301          ds.insignificance = 0.0 
2302   
2303          # The grid search size (the number of increments per dimension). 
2304          ds.GRID_INC = 8 
2305   
2306          # The do clustering. 
2307          ds.do_cluster = False 
2308   
2309          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2310          # The default value is 1e-25. 
2311          ds.set_func_tol = 1e-9 
2312   
2313          # The maximum number of iterations. 
2314          # The default value is 1e7. 
2315          ds.set_max_iter = 1000 
2316   
2317          # The verbosity level. 
2318          ds.verbosity = 1 
2319   
2320          # The rel_change WARNING level. 
2321          ds.rel_change = 0.05 
2322   
2323          # The plot_curves. 
2324          ds.plot_curves = False 
2325   
2326          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2327          ds.sherekhan_input = False 
2328   
2329          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2330          ds.opendx = False 
2331   
2332          # The set r2eff err. 
2333          ds.r2eff_err = 0.1 
2334   
2335          # The print result info. 
2336          ds.print_res = False 
2337   
2338          # Execute the script. 
2339          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2340   
2341          cur_spins = ds.data[2] 
2342          # Compare results. 
2343          for i in range(len(cur_spins)): 
2344              res_name, res_num, spin_name, params = cur_spins[i] 
2345              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2346              cur_spin = return_spin(cur_spin_id) 
2347   
2348              grid_params = ds.grid_results[i][3] 
2349              min_params = ds.min_results[i][3] 
2350              # Now read the parameters. 
2351              print("For spin: '%s'"%cur_spin_id) 
2352              for mo_param in cur_spin.params: 
2353                  # The R2 is a dictionary, depending on spectrometer frequency. 
2354                  if isinstance(getattr(cur_spin, mo_param), dict): 
2355                      grid_r2 = grid_params[mo_param] 
2356                      min_r2 = min_params[mo_param] 
2357                      set_r2 = params[mo_param] 
2358                      for key, val in list(set_r2.items()): 
2359                          grid_r2_frq = grid_r2[key] 
2360                          min_r2_frq = min_r2[key] 
2361                          set_r2_frq = set_r2[key] 
2362                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2363                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2364                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2365                          if rel_change > ds.rel_change: 
2366                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2367                              print("###################################") 
2368   
2369                          ## Make test on R2. 
2370                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 2) 
2371                  else: 
2372                      grid_val = grid_params[mo_param] 
2373                      min_val = min_params[mo_param] 
2374                      set_val = params[mo_param] 
2375                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2376                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2377                      if rel_change > ds.rel_change: 
2378                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2379                          print("###################################") 
2380   
2381                      ## Make test on parameters. 
2382                      if mo_param == 'dw': 
2383                          self.assertAlmostEqual(set_val/10, min_val/10, 1) 
2384                      elif mo_param == 'kex': 
2385                          self.assertAlmostEqual(set_val/1000, min_val/1000, 1) 
2386                      elif mo_param == 'pA': 
2387                          self.assertAlmostEqual(set_val, min_val, 3) 
2388   
2389   
2390 -    def test_cpmg_synthetic_ns3d_to_b14(self): 
2391          """Test synthetic cpmg data. 
2392   
2393          This script will produce synthetic CPMG R2eff values according to the NS CPMG 2-site 3D model, and the fit the data with B14. 
2394          Try to catch bug #22021 U{https://gna.org/bugs/index.php?22021}: Model B14 shows bad fitting to data. 
2395          """ 
2396   
2397          # Reset. 
2398          #self.interpreter.reset() 
2399   
2400          ## Set Experiments. 
2401          model_create = 'NS CPMG 2-site 3D' 
2402          #model_create = 'NS CPMG 2-site expanded' 
2403          model_analyse = 'B14' 
2404          # Exp 1 
2405          sfrq_1 = 599.8908617*1E6 
2406          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2407          time_T2_1 = 0.06 
2408          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2409          r2eff_err_1 = [0, 0, 0, 0, 0, 0, 0, 0] 
2410          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_err_1] 
2411   
2412          sfrq_2 = 499.8908617*1E6 
2413          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2414          time_T2_2 = 0.05 
2415          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2416          r2eff_err_2 = [0, 0, 0, 0, 0, 0, 0, 0] 
2417          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_err_2] 
2418   
2419          # Collect all exps 
2420          exps = [exp_1, exp_2] 
2421   
2422          spins = [ 
2423              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:10.}, 'r2a': {r20_key_1:10., r20_key_2:10.}, 'r2b': {r20_key_1:10., r20_key_2:10.}, 'kex': 1000., 'pA': 0.99, 'dw': 2.} ] 
2424              ] 
2425   
2426          # Collect the data to be used. 
2427          ds.data = [model_create, model_analyse, spins, exps] 
2428   
2429          # The tmp directory. None is the local directory. 
2430          ds.tmpdir = ds.tmpdir 
2431   
2432          # The results directory. None is the local directory. 
2433          #ds.resdir = None 
2434          ds.resdir = ds.tmpdir 
2435   
2436          # Do r20_from_min_r2eff ?. 
2437          ds.r20_from_min_r2eff = True 
2438   
2439          # Remove insignificant level. 
2440          ds.insignificance = 0.0 
2441   
2442          # The grid search size (the number of increments per dimension). 
2443          ds.GRID_INC = 8 
2444   
2445          # The do clustering. 
2446          ds.do_cluster = False 
2447   
2448          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2449          # The default value is 1e-25. 
2450          ds.set_func_tol = 1e-9 
2451   
2452          # The maximum number of iterations. 
2453          # The default value is 1e7. 
2454          ds.set_max_iter = 1000 
2455   
2456          # The verbosity level. 
2457          ds.verbosity = 1 
2458   
2459          # The rel_change WARNING level. 
2460          ds.rel_change = 0.05 
2461   
2462          # The plot_curves. 
2463          ds.plot_curves = False 
2464   
2465          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2466          ds.sherekhan_input = False 
2467   
2468          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2469          ds.opendx = False 
2470   
2471          # The set r2eff err. 
2472          ds.r2eff_err = 0.1 
2473   
2474          # The print result info. 
2475          ds.print_res = False 
2476   
2477          # Execute the script. 
2478          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2479   
2480          cur_spins = ds.data[2] 
2481          # Compare results. 
2482          for i in range(len(cur_spins)): 
2483              res_name, res_num, spin_name, params = cur_spins[i] 
2484              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2485              cur_spin = return_spin(cur_spin_id) 
2486   
2487              grid_params = ds.grid_results[i][3] 
2488              min_params = ds.min_results[i][3] 
2489              # Now read the parameters. 
2490              print("For spin: '%s'"%cur_spin_id) 
2491              for mo_param in cur_spin.params: 
2492                  # The R2 is a dictionary, depending on spectrometer frequency. 
2493                  if isinstance(getattr(cur_spin, mo_param), dict): 
2494                      grid_r2 = grid_params[mo_param] 
2495                      min_r2 = min_params[mo_param] 
2496                      set_r2 = params[mo_param] 
2497                      for key, val in list(set_r2.items()): 
2498                          grid_r2_frq = grid_r2[key] 
2499                          min_r2_frq = min_r2[key] 
2500                          set_r2_frq = set_r2[key] 
2501                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2502                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2503                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2504                          if rel_change > ds.rel_change: 
2505                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2506                              print("###################################") 
2507   
2508                          ## Make test on R2. 
2509                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 2) 
2510                  else: 
2511                      grid_val = grid_params[mo_param] 
2512                      min_val = min_params[mo_param] 
2513                      set_val = params[mo_param] 
2514                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2515                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2516                      if rel_change > ds.rel_change: 
2517                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2518                          print("###################################") 
2519   
2520                      ## Make test on parameters. 
2521                      if mo_param == 'dw': 
2522                          self.assertAlmostEqual(set_val/10, min_val/10, 5) 
2523                      elif mo_param == 'kex': 
2524                          self.assertAlmostEqual(set_val/1000, min_val/1000, 5) 
2525                      elif mo_param == 'pA': 
2526                          self.assertAlmostEqual(set_val, min_val, 6) 
2527   
2528   
2529 -    def test_cpmg_synthetic_ns3d_to_cr72_noise_cluster(self): 
2530          """Test synthetic cpmg data. For CR72 with small noise and cluster. 
2531   
2532          This script will produce synthetic CPMG R2eff values according to the selected model, and the fit the selected model. 
2533          """ 
2534   
2535          # Reset. 
2536          #self.interpreter.reset() 
2537   
2538          ## Set Experiments. 
2539          model_create = 'NS CPMG 2-site 3D' 
2540          #model_create = 'NS CPMG 2-site expanded' 
2541          model_analyse = 'CR72' 
2542   
2543          # Exp 1 
2544          sfrq_1 = 599.8908617*1E6 
2545          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2546          time_T2_1 = 0.06 
2547          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2548          r2eff_errs_1 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2549          #r2eff_errs_1 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2550          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_errs_1] 
2551   
2552          sfrq_2 = 499.8908617*1E6 
2553          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2554          time_T2_2 = 0.05 
2555          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2556          r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2557          #r2eff_errs_2 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2558          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_errs_2] 
2559   
2560          # Collect all exps 
2561          exps = [exp_1, exp_2] 
2562   
2563          spins = [ 
2564              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:11.5}, 'r2a': {r20_key_1:10., r20_key_2:11.5}, 'r2b': {r20_key_1:10., r20_key_2:11.5}, 'kex': 1000., 'pA': 0.99, 'dw': 2.} ], 
2565              ['Ala', 2, 'N', {'r2': {r20_key_1:13., r20_key_2:14.5}, 'r2a': {r20_key_1:13., r20_key_2:14.5}, 'r2b': {r20_key_1:13., r20_key_2:14.5}, 'kex': 1000., 'pA': 0.99, 'dw': 1.} ] 
2566              ] 
2567   
2568          # Collect the data to be used. 
2569          ds.data = [model_create, model_analyse, spins, exps] 
2570   
2571          # The tmp directory. None is the local directory. 
2572          ds.tmpdir = ds.tmpdir 
2573   
2574          # The results directory. None is the local directory. 
2575          #ds.resdir = None 
2576          ds.resdir = ds.tmpdir 
2577   
2578          # Do r20_from_min_r2eff ?. 
2579          ds.r20_from_min_r2eff = True 
2580   
2581          # Remove insignificant level. 
2582          ds.insignificance = 0.0 
2583   
2584          # The grid search size (the number of increments per dimension). 
2585          ds.GRID_INC = 13 
2586   
2587          # The do clustering. 
2588          ds.do_cluster = True 
2589   
2590          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2591          # The default value is 1e-25. 
2592          ds.set_func_tol = 1e-8 
2593   
2594          # The maximum number of iterations. 
2595          # The default value is 1e7. 
2596          ds.set_max_iter = 10000 
2597   
2598          # The verbosity level. 
2599          ds.verbosity = 1 
2600   
2601          # The rel_change WARNING level. 
2602          ds.rel_change = 0.05 
2603   
2604          # The plot_curves. 
2605          ds.plot_curves = False 
2606   
2607          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2608          ds.sherekhan_input = False 
2609   
2610          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2611          ds.opendx = False 
2612   
2613          # The set r2eff err. 
2614          ds.r2eff_err = 0.1 
2615   
2616          # The print result info. 
2617          ds.print_res = False 
2618   
2619          # Execute the script. 
2620          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2621   
2622          cur_spins = ds.data[2] 
2623          # Compare results. 
2624          for i in range(len(cur_spins)): 
2625              res_name, res_num, spin_name, params = cur_spins[i] 
2626              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2627              cur_spin = return_spin(cur_spin_id) 
2628   
2629              grid_params = ds.grid_results[i][3] 
2630   
2631              # Extract the clust results. 
2632              min_params = ds.clust_results[i][3] 
2633              # Now read the parameters. 
2634              print("For spin: '%s'"%cur_spin_id) 
2635              for mo_param in cur_spin.params: 
2636                  # The R2 is a dictionary, depending on spectrometer frequency. 
2637                  if isinstance(getattr(cur_spin, mo_param), dict): 
2638                      grid_r2 = grid_params[mo_param] 
2639                      min_r2 = min_params[mo_param] 
2640                      set_r2 = params[mo_param] 
2641                      for key, val in list(set_r2.items()): 
2642                          grid_r2_frq = grid_r2[key] 
2643                          min_r2_frq = min_r2[key] 
2644                          set_r2_frq = set_r2[key] 
2645                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2646                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2647                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2648                          if rel_change > ds.rel_change: 
2649                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2650                              print("###################################") 
2651   
2652                          ## Make test on R2. 
2653                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 1) 
2654                  else: 
2655                      grid_val = grid_params[mo_param] 
2656                      min_val = min_params[mo_param] 
2657                      set_val = params[mo_param] 
2658                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2659                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2660                      if rel_change > ds.rel_change: 
2661                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2662                          print("###################################") 
2663   
2664                      ## Make test on parameters. 
2665                      if mo_param == 'dw': 
2666                          self.assertAlmostEqual(set_val/10, min_val/10, 1) 
2667                      elif mo_param == 'kex': 
2668                          self.assertAlmostEqual(set_val/1000, min_val/1000, 1) 
2669                      elif mo_param == 'pA': 
2670                          self.assertAlmostEqual(set_val, min_val, 2) 
2671   
2672   
2673 -    def test_cpmg_synthetic_dx_map_points(self): 
2674          """Test synthetic cpmg data, calling the dx.map function with one or two points. 
2675   
2676          This script will produce synthetic CPMG R2eff values according to the selected model, and the fit the selected model. 
2677          """ 
2678   
2679          # Reset. 
2680          #self.interpreter.reset() 
2681   
2682          ## Set Experiments. 
2683          model_create = MODEL_NS_CPMG_2SITE_EXPANDED 
2684          model_analyse = 'CR72' 
2685          # Exp 1 
2686          sfrq_1 = 599.8908617*1E6 
2687          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2688          time_T2_1 = 0.06 
2689          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2690          r2eff_err_1 = [0, 0, 0, 0, 0, 0, 0, 0] 
2691          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_err_1] 
2692   
2693          sfrq_2 = 499.8908617*1E6 
2694          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2695          time_T2_2 = 0.05 
2696          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2697          r2eff_err_2 = [0, 0, 0, 0, 0, 0, 0, 0] 
2698          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_err_2] 
2699   
2700          # Collect all exps 
2701          exps = [exp_1, exp_2] 
2702   
2703          spins = [ 
2704              ['Ala', 1, 'N', {'r2': {r20_key_1:2, r20_key_2:2}, 'r2a': {r20_key_1:2, r20_key_2:2}, 'r2b': {r20_key_1:2, r20_key_2:2}, 'kex': 1000, 'pA': 0.99, 'dw': 2} ] 
2705              ] 
2706   
2707          # Collect the data to be used. 
2708          ds.data = [model_create, model_analyse, spins, exps] 
2709   
2710          # The tmp directory. None is the local directory. 
2711          ds.tmpdir = ds.tmpdir 
2712   
2713          # The results directory. None is the local directory. 
2714          #ds.resdir = None 
2715          ds.resdir = ds.tmpdir 
2716   
2717          # Do r20_from_min_r2eff ?. 
2718          ds.r20_from_min_r2eff = True 
2719   
2720          # Remove insignificant level. 
2721          ds.insignificance = 0.0 
2722   
2723          # The grid search size (the number of increments per dimension). 
2724          ds.GRID_INC = None 
2725   
2726          # The do clustering. 
2727          ds.do_cluster = False 
2728   
2729          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2730          # The default value is 1e-25. 
2731          ds.set_func_tol = 1e-9 
2732   
2733          # The maximum number of iterations. 
2734          # The default value is 1e7. 
2735          ds.set_max_iter = 1000 
2736   
2737          # The verbosity level. 
2738          ds.verbosity = 1 
2739   
2740          # The rel_change WARNING level. 
2741          ds.rel_change = 0.05 
2742   
2743          # The plot_curves. 
2744          ds.plot_curves = False 
2745   
2746          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2747          ds.sherekhan_input = False 
2748   
2749          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2750          ds.opendx = False 
2751   
2752          # The set r2eff err. 
2753          ds.r2eff_err = 0.1 
2754   
2755          # The print result info. 
2756          ds.print_res = False 
2757   
2758          # Execute the script. 
2759          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2760   
2761          # Get the spins. 
2762          cur_spins = ds.data[2] 
2763   
2764          # First switch pipe, since dx.map will go through parameters and end up a "bad" place. :-) 
2765          ds.pipe_name_MODEL_MAP = "%s_%s_map"%(ds.pipe_name, model_analyse) 
2766          self.interpreter.pipe.copy(pipe_from=ds.pipe_name, pipe_to=ds.pipe_name_MODEL_MAP, bundle_to = ds.pipe_bundle) 
2767          self.interpreter.pipe.switch(pipe_name=ds.pipe_name_MODEL_MAP) 
2768   
2769          # Copy R2eff, but not the original parameters 
2770          self.interpreter.value.copy(pipe_from=ds.pipe_name_r2eff, pipe_to=ds.pipe_name_MODEL_MAP, param='r2eff') 
2771   
2772          # Then select model. 
2773          self.interpreter.relax_disp.select_model(model=model_analyse) 
2774   
2775          # Define dx.map settings. 
2776          ds.dx_inc = 4 
2777          ds.dx_params = ['dw', 'pA', 'kex'] 
2778   
2779          res_name, res_num, spin_name, params = cur_spins[0] 
2780          cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2781          cur_spin = return_spin(cur_spin_id) 
2782   
2783          print("Params for dx map is") 
2784          print(ds.dx_params) 
2785          print("Point param for dx map is") 
2786          print(ds.dx_set_val) 
2787          cur_model = model_analyse.replace(' ', '_') 
2788          file_name_map = "%s_map%s" % (cur_model, cur_spin_id.replace('#', '_').replace(':', '_').replace('@', '_')) 
2789          file_name_point = "%s_point%s" % (cur_model, cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_')) 
2790          self.interpreter.dx.map(params=ds.dx_params, map_type='Iso3D', spin_id=cur_spin_id, inc=ds.dx_inc, lower=None, upper=None, axis_incs=10, file_prefix=file_name_map, dir=ds.resdir, point=[ds.dx_set_val, ds.dx_clust_val], point_file=file_name_point, create_par_file=True) 
2791   
2792          ## Check for file creation 
2793          # Set filepaths. 
2794          map_cfg = ds.tmpdir+sep+file_name_map+".cfg" 
2795          map_net = ds.tmpdir+sep+file_name_map+".net" 
2796          map_general = ds.tmpdir+sep+file_name_map+".general" 
2797          map_par = get_file_path(file_name=file_name_map+".par", dir=ds.tmpdir) 
2798          map_plot = get_file_path(file_name=file_name_map+".py", dir=ds.tmpdir) 
2799   
2800          point_general = ds.tmpdir+sep+file_name_point+".general" 
2801          point_point = ds.tmpdir+sep+file_name_point 
2802          point_par = get_file_path(file_name=file_name_point+".par", dir=ds.tmpdir) 
2803   
2804          # Test the files exists. 
2805          self.assert_(access(map_cfg, F_OK)) 
2806          self.assert_(access(map_net, F_OK)) 
2807          self.assert_(access(map_general, F_OK)) 
2808          self.assert_(access(map_par, F_OK)) 
2809          self.assert_(access(map_plot, F_OK)) 
2810          self.assert_(access(point_general, F_OK)) 
2811          self.assert_(access(point_point, F_OK)) 
2812          self.assert_(access(point_par, F_OK)) 
2813   
2814          # Open the files for testing. 
2815          # Check the cfg file. 
2816          print("\nChecking the dx map .cfg file.") 
2817          res_file = [ 
2818              '//'+"\n", 
2819              '//'+"\n", 
2820              '// time: Thu May  8 18:55:31 2014'+"\n", 
2821              '//'+"\n", 
2822              '// version: 3.2.0 (format), 4.3.2 (DX)'+"\n", 
2823              '//'+"\n", 
2824              '//'+"\n", 
2825              '// panel[0]: position = (0.0164,0.0000), size = 0.2521x0.1933, startup = 1, devstyle = 1'+"\n", 
2826              '// title: value = Control Panel'+"\n", 
2827              '//'+"\n", 
2828              '// workspace: width = 251, height = 142'+"\n", 
2829              '// layout: snap = 0, width = 50, height = 50, align = NN'+"\n", 
2830              '//'+"\n", 
2831              '// interactor Selector[1]: num_components = 1, value = 1 '+"\n", 
2832              '// selections: maximum = 2, current = 0 '+"\n", 
2833              '// option[0]: name = "Colour", value = 1'+"\n", 
2834              '// option[1]: name = "Grey", value = 2'+"\n", 
2835              '// instance: panel = 0, x = 81, y = 6, style = Scrolled List, vertical = 1, size = 170x136'+"\n", 
2836              '// label: value = Colour Selector'+"\n", 
2837              '//'+"\n", 
2838              '// node Image[3]:'+"\n", 
2839              '// title: value = Surface'+"\n", 
2840              '// depth: value = 24'+"\n", 
2841              '// window: position = (0.0000,0.0400), size = 0.9929x0.9276'+"\n", 
2842          ] 
2843          file = open(map_cfg, 'r') 
2844          lines = file.readlines() 
2845          file.close() 
2846          for i in range(len(res_file)): 
2847              # Skip time point 
2848              if i == 2: 
2849                  continue 
2850              self.assertEqual(res_file[i], lines[i]) 
2851   
2852          print("\nChecking the dx map .general file.") 
2853          res_file = [ 
2854              'file = CR72_map_1_N'+"\n", 
2855              'grid = 5 x 5 x 5'+"\n", 
2856              'format = ascii'+"\n", 
2857              'interleaving = field'+"\n", 
2858              'majority = row'+"\n", 
2859              'field = data'+"\n", 
2860              'structure = scalar'+"\n", 
2861              'type = float'+"\n", 
2862              'dependency = positions'+"\n", 
2863              'positions = regular, regular, regular, 0, 1, 0, 1, 0, 1'+"\n", 
2864              ''+"\n", 
2865              'end'+"\n", 
2866          ] 
2867          file = open(map_general, 'r') 
2868          lines = file.readlines() 
2869          file.close() 
2870          for i in range(len(res_file)): 
2871              # Skip time point 
2872              #if i == 2: 
2873              #    continue 
2874              self.assertEqual(res_file[i], lines[i]) 
2875   
2876          print("\nChecking the dx point .general file.") 
2877          res_file = [ 
2878              'file = CR72_point_1_N'+"\n", 
2879              'points = 2'+"\n", 
2880              'format = ascii'+"\n", 
2881              'interleaving = field'+"\n", 
2882              'field = locations, field0'+"\n", 
2883              'structure = 3-vector, scalar'+"\n", 
2884              'type = float, float'+"\n", 
2885              ''+"\n", 
2886              'end'+"\n", 
2887          ] 
2888          file = open(point_general, 'r') 
2889          lines = file.readlines() 
2890          file.close() 
2891          for i in range(len(res_file)): 
2892              # Skip time point 
2893              #if i == 2: 
2894              #    continue 
2895              self.assertEqual(res_file[i], lines[i]) 
2896   
2897          print("\nChecking the dx point point file.") 
2898          res_file = [ 
2899              '0.8            3.92           0.39964        1'+"\n", 
2900              '0.76981        3.9169         0.41353        1'+"\n", 
2901          ] 
2902          file = open(point_point, 'r') 
2903          lines = file.readlines() 
2904          file.close() 
2905          for i in range(len(res_file)): 
2906              # Skip time point 
2907              #if i == 2: 
2908              #    continue 
2909              self.assertEqual(res_file[i], lines[i]) 
2910   
2911          print("\nChecking the dx point par file.") 
2912          res_file = [ 
2913              '# i    dw         pA         kex           chi2          i_sort    dw_sort    pA_sort    kex_sort      chi2_sort     '+"\n", 
2914              '0      2.00000    0.99000    1000.00000    6185.84926    0         2.00000    0.99000    1000.00000    6185.84926    '+"\n", 
2915              '1      1.92453    0.98961    1034.72206    6396.02770    1         1.92453    0.98961    1034.72206    6396.02770    '+"\n", 
2916          ] 
2917          res_file2 = [ 
2918              '# i    dw         pA         kex           chi2          i_sort    dw_sort    pA_sort    kex_sort      chi2_sort     '+"\n", 
2919              '0      2.00000    0.99000    1000.00000    6185.84926    0         2.00000    0.99000    1000.00000    6185.84926    '+"\n", 
2920              '1      1.92452    0.98961    1034.72424    6396.02439    1         1.92452    0.98961    1034.72424    6396.02439    '+"\n", 
2921          ]  # Python 2.5 and 3.1. 
2922          file = open(point_par, 'r') 
2923          lines = file.readlines() 
2924          file.close() 
2925          for i in range(len(res_file)): 
2926              if lines[i] != res_file[i] and lines[i] != res_file2[i]: 
2927                  self.assertEqual(res_file[i], lines[i]) 
2928   
2929          print("\nChecking the matplotlib surface plot file.") 
2930          res_file = [ 
2931              'from copy import deepcopy'+"\n", 
2932              'import numpy as np'+"\n", 
2933              'import scipy.interpolate'+"\n", 
2934              'from numpy.ma import masked_where'+"\n", 
2935              ''+"\n", 
2936              'from mpl_toolkits.mplot3d import axes3d'+"\n", 
2937              'import matplotlib.pyplot as plt'+"\n", 
2938              'from matplotlib import cm'+"\n", 
2939              ''+"\n", 
2940              '# Open file and get header.'+"\n", 
2941              'mapfile_name = "%s.par"'%file_name_map+"\n", 
2942              'pointfile_name = "%s.par"'%file_name_point+"\n", 
2943              ''+"\n", 
2944          ] 
2945          file = open(map_plot, 'r') 
2946          lines = file.readlines() 
2947          file.close() 
2948          for i in range(len(res_file)): 
2949              self.assertEqual(res_file[i], lines[i]) 
2950   
2951   
2952 -    def test_curve_type_cpmg_fixed_time(self): 
2953          """Test the curve type detection using the Dr. Flemming Hansen's CPMG fixed time test data.""" 
2954   
2955          # Reset. 
2956          self.interpreter.reset() 
2957   
2958          # Load the base data. 
2959          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen' 
2960          self.interpreter.state.load(data_path+sep+'r2eff_values') 
2961   
2962          # The type. 
2963          curve_type = get_curve_type(id='500_133.33.in') 
2964          self.assertEqual(curve_type, 'fixed time') 
2965   
2966   
2967 -    def test_curve_type_r1rho_exponential(self, model=None): 
2968          """Test the curve type detection using the 'M61' exponential test data.""" 
2969   
2970          # Reset. 
2971          self.interpreter.reset() 
2972   
2973          # Load the base data. 
2974          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r1rho_on_res_m61' 
2975          self.interpreter.state.load(data_path+sep+'r2eff_values') 
2976   
2977          # The type. 
2978          curve_type = get_curve_type(id='nu_2000_ncyc9') 
2979          self.assertEqual(curve_type, 'exponential') 
2980   
2981   
2982 -    def test_curve_type_r1rho_fixed_time(self, model=None): 
2983          """Test the curve type detection using the 'TP02' fixed time test data.""" 
2984   
2985          # Reset. 
2986          self.interpreter.reset() 
2987   
2988          # Load the base data. 
2989          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r1rho_off_res_tp02' 
2990          self.interpreter.state.load(data_path+sep+'r2eff_values') 
2991   
2992          # The type. 
2993          curve_type = get_curve_type(id='nu_1000.0_500MHz') 
2994          self.assertEqual(curve_type, 'fixed time') 
2995   
2996   
2997 -    def test_dpl94_data_to_dpl94(self): 
2998          """Test the relaxation dispersion 'DPL94' model curve fitting to fixed time synthetic data.""" 
2999   
3000          # Fixed time variable. 
3001          ds.fixed = True 
3002   
3003          # Execute the script. 
3004          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_dpl94.py') 
3005   
3006          # The original parameters. 
3007          i0 = [100000.0, 20000.0] 
3008          r1rho_prime = [2.25, 24.0] 
3009          pA = 0.7 
3010          kex = 1000.0 
3011          delta_omega = [1.0, 2.0] 
3012          phi_ex = [] 
3013          for i in range(2): 
3014              phi_ex.append(pA * (1.0 - pA) * delta_omega[i]**2) 
3015   
3016          # Switch to the 'DPL94' model data pipe, then check for each spin. 
3017          self.interpreter.pipe.switch('DPL94 - relax_disp') 
3018          spin_index = 0 
3019          for spin, spin_id in spin_loop(return_id=True): 
3020              # Printout. 
3021              print("\nSpin %s." % spin_id) 
3022   
3023              # Check the fitted parameters. 
3024              self.assertAlmostEqual(spin.r2['R1rho - 800.00000000 MHz']/10, r1rho_prime[spin_index]/10, 2) 
3025              self.assertAlmostEqual(spin.phi_ex, phi_ex[spin_index], 2) 
3026              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 
3027   
3028              # Increment the spin index. 
3029              spin_index += 1 
3030   
3031   
3032 -    def test_dx_map_clustered(self): 
3033          """Test making dx_map for residues under clustered calculation. 
3034   
3035          This uses CPMG data from: 
3036              - Webb H, Tynan-Connolly BM, Lee GM, Farrell D, O'Meara F, Soendergaard CR, Teilum K, Hewage C, McIntosh LP, Nielsen JE 
3037                Remeasuring HEWL pK(a) values by NMR spectroscopy: methods, analysis, accuracy, and implications for theoretical pK(a) calculations. 
3038                (2011), Proteins: Struct, Funct, Bioinf 79(3):685-702, U{DOI 10.1002/prot.22886<http://dx.doi.org/10.1002/prot.22886>} 
3039          """ 
3040   
3041          # Define path to data  
3042          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'HWebb_KTeilum_Proteins_Struct_Funct_Bioinf_2011' 
3043   
3044          # Read data. 
3045          self.interpreter.results.read(prev_data_path + sep + 'FT_-_CR72_-_min_-_128_-_free_spins') 
3046   
3047          # Get residue of interest. 
3048          cur_spin_id = ":%i@%s"%(52, 'N') 
3049          cur_spin_id_str = cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_') 
3050   
3051          # Get the spin container. 
3052          cur_spin = return_spin(cur_spin_id) 
3053   
3054          # Get the chi2 value 
3055          pre_chi2 = cur_spin.chi2 
3056   
3057          # Then do a local minimisation. 
3058          #self.interpreter.select.spin(":%i@%s"%(2, 'N')) 
3059          self.interpreter.minimise.calculate() 
3060   
3061          # Get the chi2 value after calculation. 
3062          calc_chi2 = cur_spin.chi2 
3063   
3064          # Assert calculation is equal. 
3065          self.assertAlmostEqual(pre_chi2, calc_chi2) 
3066   
3067          # Define dx.map settings. 
3068          dx_inc = 2 
3069          dx_inc_sides = dx_inc / 2 
3070   
3071          dx_params = ['dw', 'pA', 'kex'] 
3072          dx_point_clustered_min = [cur_spin.dw, cur_spin.pA, cur_spin.kex] 
3073   
3074          print("Params for dx map is") 
3075          print(dx_params) 
3076          print("Point param for dx map is, with chi2=%3.3f"%pre_chi2) 
3077          print(dx_point_clustered_min) 
3078   
3079          # Define file_names. 
3080          cur_model = 'CR72' 
3081          file_name_map = "%s_map%s" % (cur_model, cur_spin_id_str) 
3082          file_name_point = "%s_point%s" % (cur_model, cur_spin_id_str) 
3083   
3084          # Step-size of parameter is 10 % 
3085          param_delta = 0.1 
3086   
3087          # Determine bounds for lower and upper 
3088          lower = [] 
3089          upper = [] 
3090          for i, param_val in enumerate(dx_point_clustered_min): 
3091              param = dx_params[i] 
3092              step_val = param_delta * param_val 
3093              step_length = step_val * dx_inc_sides 
3094   
3095              # Calculate value 
3096              low_val = param_val - step_length 
3097              lower.append(low_val) 
3098   
3099              upp_val = param_val + step_length 
3100              upper.append(upp_val) 
3101   
3102              print("For param %s, lower=%3.3f, upper=%3.3f, step_value=%3.3f, steps=%i, centered at=%3.3f"% (param, low_val, upp_val, step_val, dx_inc, param_val)) 
3103   
3104          # If the number of increments are 2, there will be 3 point calculations per parameter. 
3105          # Since we have ordered the lower and upper limits on sides of the parameter, the middle index should give us the expected global value. 
3106          dx_param_indexes = dx_inc + 1 
3107          dx_point_index = dx_inc_sides + 1 
3108   
3109          # Find the line number. 
3110          line = 1 
3111          for i in range(1, dx_param_indexes + 1): 
3112              for j in range(1, dx_param_indexes + 1): 
3113                  for k in range(1, dx_param_indexes + 1): 
3114                      if i == dx_point_index and j == dx_point_index and k == dx_point_index: 
3115                          line_chi2 = line 
3116                      # Add to line counter. 
3117                      line += 1 
3118   
3119          # Define temporary folder. 
3120          result_dir = self.tmpdir 
3121   
3122          # For testing. 
3123          #result_dir = None 
3124          #lower = None 
3125          #upper = None 
3126          #self.interpreter.relax_disp.cluster(cluster_id='free spins', spin_id=cur_spin_id) 
3127   
3128   
3129          # Then do the map. 
3130          self.interpreter.dx.map(params=dx_params, map_type='Iso3D', spin_id=cur_spin_id, inc=dx_inc, lower=lower, upper=upper, axis_incs=10, file_prefix=file_name_map, dir=result_dir, point=dx_point_clustered_min, point_file=file_name_point) 
3131   
3132          # Print where to locate values. 
3133          nr_chi2_val = dx_param_indexes**3 
3134          print("Nr of chi2 calculations are=%i"%nr_chi2_val) 
3135          print("Global chi2=%3.3f, Calc_chi=%3.3f, map_line_chi2=%i" % (pre_chi2, calc_chi2, line_chi2) ) 
3136   
3137          ## Check for file creation 
3138          # Set filepaths. 
3139          map_name = get_file_path(file_name=file_name_map, dir=result_dir) 
3140          map_cfg = get_file_path(file_name=file_name_map+".cfg", dir=result_dir) 
3141          map_net = get_file_path(file_name=file_name_map+".net", dir=result_dir) 
3142          map_general = get_file_path(file_name=file_name_map+".general", dir=result_dir) 
3143   
3144          point_general = get_file_path(file_name=file_name_point+".general", dir=result_dir) 
3145          point_point = get_file_path(file_name=file_name_point, dir=result_dir) 
3146   
3147          # Test the files exists. 
3148          self.assert_(access(map_cfg, F_OK)) 
3149          self.assert_(access(map_net, F_OK)) 
3150          self.assert_(access(map_general, F_OK)) 
3151          self.assert_(access(point_general, F_OK)) 
3152          self.assert_(access(point_point, F_OK)) 
3153   
3154          # Open the file, and assert the chi2 value is as expected. 
3155          get_data = extract_data(file=map_name) 
3156   
3157          # Extract line 0, column 0. 
3158          test = float(get_data[line_chi2-1][0]) 
3159   
3160          # Assert. 
3161          self.assertAlmostEqual(test, pre_chi2,  6) 
3162   
3163   
3164 -    def test_dx_map_clustered_create_par_file(self): 
3165          """Test making dx_map for residues under clustered calculation, and the creation of the parameter file. 
3166   
3167          U{Task #7860<https://gna.org/task/index.php?7860>} : When dx_map is issued, create a parameter file which maps parameters to chi2 value. 
3168   
3169          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
3170          """ 
3171   
3172          # Define path to data  
3173          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'KTeilum_FMPoulsen_MAkke_2006'+sep+'surface_chi2_clustered_fitting' 
3174   
3175          # Read data. 
3176          self.interpreter.results.read(prev_data_path + sep + 'coMDD_-_TSMFK01_-_min_-_32_-_free_spins.bz2') 
3177   
3178          # Get residue of interest. 
3179          cur_spin_id = ":%i@%s"%(65, 'N') 
3180          cur_spin_id_str = cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_') 
3181   
3182          # Get the spin container. 
3183          cur_spin = return_spin(cur_spin_id) 
3184   
3185          # Get the chi2 value 
3186          pre_chi2 = cur_spin.chi2 
3187   
3188          # Then do a local minimisation. 
3189          #self.interpreter.select.spin(":%i@%s"%(2, 'N')) 
3190          self.interpreter.minimise.calculate() 
3191   
3192          # Get the chi2 value after calculation. 
3193          calc_chi2 = cur_spin.chi2 
3194   
3195          # Assert calculation is equal. 
3196          self.assertAlmostEqual(pre_chi2, calc_chi2) 
3197   
3198          # Define dx.map settings. 
3199          dx_inc = 2 
3200          dx_params = ['dw', 'k_AB', 'r2a'] 
3201          dx_point_clustered_min = [cur_spin.dw, cur_spin.k_AB, cur_spin.r2a['SQ CPMG - 499.86214000 MHz']] 
3202   
3203          print("Params for dx map is") 
3204          print(dx_params) 
3205          print("Point param for dx map is, with chi2=%3.3f"%pre_chi2) 
3206          print(dx_point_clustered_min) 
3207   
3208          # Define file_names. 
3209          cur_model = 'TSMFK01' 
3210          file_name_map = "%s_map%s" % (cur_model, cur_spin_id_str) 
3211          file_name_point = "%s_point%s" % (cur_model, cur_spin_id_str) 
3212   
3213          # Determine bounds for lower and upper 
3214          lower = [dx_point_clustered_min[0], dx_point_clustered_min[1], dx_point_clustered_min[2]] 
3215          upper = [19.0, 2.4, 9.5] 
3216   
3217          # Define temporary folder. 
3218          result_dir = self.tmpdir 
3219   
3220          # For testing. 
3221          #result_dir = None 
3222          #self.interpreter.relax_disp.cluster(cluster_id='free spins', spin_id=cur_spin_id) 
3223   
3224          # Then do the map. 
3225          self.interpreter.dx.map(params=dx_params, map_type='Iso3D', spin_id=cur_spin_id, inc=dx_inc, lower=lower, upper=upper, axis_incs=10, file_prefix=file_name_map, dir=result_dir, point=dx_point_clustered_min, point_file=file_name_point, create_par_file=True) 
3226   
3227          # Print where to locate values. 
3228          nr_chi2_val = (dx_inc + 1)**3 
3229          print("Nr of chi2 calculations are=%i"%nr_chi2_val) 
3230          print("Global chi2=%3.3f, Calc_chi=%3.3f" % (pre_chi2, calc_chi2) ) 
3231   
3232          ## Check for file creation 
3233          # Set filepaths. 
3234          map_name = get_file_path(file_name=file_name_map, dir=result_dir) 
3235          map_cfg = get_file_path(file_name=file_name_map+".cfg", dir=result_dir) 
3236          map_net = get_file_path(file_name=file_name_map+".net", dir=result_dir) 
3237          map_general = get_file_path(file_name=file_name_map+".general", dir=result_dir) 
3238          map_par = get_file_path(file_name=file_name_map+".par", dir=result_dir) 
3239   
3240          point_general = get_file_path(file_name=file_name_point+".general", dir=result_dir) 
3241          point_point = get_file_path(file_name=file_name_point, dir=result_dir) 
3242   
3243          # Test the files exists. 
3244          self.assert_(access(map_cfg, F_OK)) 
3245          self.assert_(access(map_net, F_OK)) 
3246          self.assert_(access(map_general, F_OK)) 
3247          self.assert_(access(map_par, F_OK)) 
3248          self.assert_(access(point_general, F_OK)) 
3249          self.assert_(access(point_point, F_OK)) 
3250   
3251          print("\nParams for dx map is") 
3252          print(dx_params) 
3253          print("Point param for dx map is, with chi2=%3.3f"%pre_chi2) 
3254          print(dx_point_clustered_min, "\n") 
3255   
3256          # Open the parameter chi2 file, and assert the chi2 value in the sorted parameter file is not lower that than the global minimisation. 
3257          get_data = extract_data(file=map_par) 
3258   
3259          # Extract line 1, column 9. 
3260          test = float(get_data[1][9]) 
3261   
3262          # Print data if map contain a lower value than the global minimised value. 
3263          if test < pre_chi2: 
3264              print("\nInitial clustered minimised chi2 value is=%3.3f, whereby the minimum map value is=%3.3f\n" % (pre_chi2, test)) 
3265              for line in get_data: 
3266                  print(line) 
3267   
3268          # Assert that the initial global chi2 is lower than the map value. 
3269   
3270          # The following test was taken out, since this a particular interesting case. 
3271          # There exist a double minimum, where relax has not found the global minimum. 
3272          # This is due to not grid searching for R2A, but using the minimum  
3273          #self.assert_(pre_chi2 < test) 
3274   
3275   
3276 -    def test_estimate_r2eff_err(self): 
3277          """Test the user function for estimating R2eff errors from exponential curve fitting. 
3278   
3279          This follows Task 7822. 
3280          U{task #7822<https://gna.org/task/index.php?7822>}: Implement user function to estimate R2eff and associated errors for exponential curve fitting. 
3281   
3282          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
3283          Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
3284          """ 
3285   
3286          # Cluster residues 
3287          cluster_ids = [ 
3288          ":13@N", 
3289          ":15@N", 
3290          ":16@N", 
3291          ":25@N", 
3292          ":26@N", 
3293          ":28@N", 
3294          ":39@N", 
3295          ":40@N", 
3296          ":41@N", 
3297          ":43@N", 
3298          ":44@N", 
3299          ":45@N", 
3300          ":49@N", 
3301          ":52@N", 
3302          ":53@N"] 
3303   
3304          # Load the data. 
3305          self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids, read_R1=False) 
3306   
3307          # The dispersion models. 
3308          MODELS = [MODEL_NOREX, MODEL_DPL94, MODEL_TP02, MODEL_TAP03, MODEL_MP05, MODEL_NS_R1RHO_2SITE] 
3309   
3310          # The grid search size (the number of increments per dimension). 
3311          GRID_INC = None 
3312   
3313          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
3314          MC_NUM = 3 
3315   
3316          # Model selection technique. 
3317          MODSEL = 'AIC' 
3318   
3319          # Execute the auto-analysis (fast). 
3320          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
3321          OPT_FUNC_TOL = 1e-25 
3322          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
3323          OPT_MAX_ITERATIONS = 10000000 
3324          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
3325   
3326          result_dir_name = ds.tmpdir 
3327   
3328          # Make all spins free 
3329          for curspin in cluster_ids: 
3330              self.interpreter.relax_disp.cluster('free spins', curspin) 
3331              # Shut them down 
3332              self.interpreter.deselect.spin(spin_id=curspin, change_all=False) 
3333   
3334          # Select only a subset of spins for global fitting 
3335          #self.interpreter.select.spin(spin_id=':41@N', change_all=False) 
3336          #self.interpreter.relax_disp.cluster('model_cluster', ':41@N') 
3337   
3338          #self.interpreter.select.spin(spin_id=':40@N', change_all=False) 
3339          #self.interpreter.relax_disp.cluster('model_cluster', ':40@N') 
3340   
3341          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
3342          #self.interpreter.relax_disp.cluster('model_cluster', ':52@N') 
3343   
3344          # Set the model. 
3345          self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
3346   
3347          # Check if intensity errors have already been calculated. 
3348          check_intensity_errors() 
3349   
3350          # Do a grid search. 
3351          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=11, constraints=True, verbosity=1) 
3352   
3353          # Minimise. 
3354          self.interpreter.minimise.execute(min_algor='Newton', constraints=False, verbosity=1) 
3355   
3356          # Estimate R2eff errors. 
3357          self.interpreter.relax_disp.r2eff_err_estimate() 
3358   
3359          r1_fit = True 
3360   
3361          # Run the analysis. 
3362          relax_disp.Relax_disp(pipe_name=ds.pipe_name, pipe_bundle=ds.pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL, r1_fit=r1_fit) 
3363   
3364          # Verify the data. 
3365          self.verify_r1rho_kjaergaard_missing_r1(models=MODELS, result_dir_name=result_dir_name, r2eff_estimate='direct') 
3366   
3367   
3368 -    def test_estimate_r2eff_err_auto(self): 
3369          """Test the user function for estimating R2eff errors from exponential curve fitting, via the auto_analyses menu. 
3370   
3371          This follows Task 7822. 
3372          U{task #7822<https://gna.org/task/index.php?7822>}: Implement user function to estimate R2eff and associated errors for exponential curve fitting. 
3373   
3374          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
3375          Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
3376          """ 
3377   
3378          # Cluster residues 
3379          cluster_ids = [ 
3380          ":13@N", 
3381          ":15@N", 
3382          ":16@N", 
3383          ":25@N", 
3384          ":26@N", 
3385          ":28@N", 
3386          ":39@N", 
3387          ":40@N", 
3388          ":41@N", 
3389          ":43@N", 
3390          ":44@N", 
3391          ":45@N", 
3392          ":49@N", 
3393          ":52@N", 
3394          ":53@N"] 
3395   
3396          # Load the data. 
3397          #self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids, read_R1=False) 
3398          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013'+sep 
3399   
3400          # Set pipe name, bundle and type. 
3401          pipe_name = 'base pipe' 
3402          pipe_bundle = 'relax_disp' 
3403          pipe_type = 'relax_disp' 
3404   
3405          # Create the data pipe. 
3406          self.interpreter.pipe.create(pipe_name=pipe_name, bundle=pipe_bundle, pipe_type=pipe_type) 
3407   
3408          file = data_path + '1_setup_r1rho_GUI.py' 
3409          self.interpreter.script(file=file, dir=None) 
3410   
3411          # The dispersion models. 
3412          MODELS = [MODEL_R2EFF, MODEL_NOREX, MODEL_DPL94, MODEL_TP02, MODEL_TAP03, MODEL_MP05, MODEL_NS_R1RHO_2SITE] 
3413   
3414          # The grid search size (the number of increments per dimension). 
3415          GRID_INC = None 
3416   
3417          # The number of Monte Carlo simulations to be used for error analysis for exponential curve fitting of R2eff. 
3418          # When set to minus 1, estimation of the errors will be extracted from the covariance matrix. 
3419          # This is HIGHLY likely to be wrong, but can be used in an initial test fase. 
3420          EXP_MC_NUM = -1 
3421   
3422          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
3423          MC_NUM = 3 
3424   
3425          # Model selection technique. 
3426          MODSEL = 'AIC' 
3427   
3428          # Execute the auto-analysis (fast). 
3429          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
3430          OPT_FUNC_TOL = 1e-25 
3431          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
3432          OPT_MAX_ITERATIONS = 10000000 
3433          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
3434   
3435          # Make all spins free 
3436          #for curspin in cluster_ids: 
3437          #    self.interpreter.relax_disp.cluster('free spins', curspin) 
3438          #    # Shut them down 
3439          #    self.interpreter.deselect.spin(spin_id=curspin, boolean='OR', change_all=False) 
3440   
3441          # Make all spins free 
3442          self.interpreter.deselect.spin(spin_id=':1-100', change_all=False) 
3443   
3444          # Select only a subset of spins for global fitting 
3445          #self.interpreter.select.spin(spin_id=':41@N', change_all=False) 
3446          #self.interpreter.relax_disp.cluster('model_cluster', ':41@N') 
3447   
3448          #self.interpreter.select.spin(spin_id=':40@N', change_all=False) 
3449          #self.interpreter.relax_disp.cluster('model_cluster', ':40@N') 
3450   
3451          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
3452          #self.interpreter.relax_disp.cluster('model_cluster', ':52@N') 
3453   
3454          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3455              print(spin_id) 
3456   
3457          result_dir_name = self.tmpdir 
3458          r1_fit = True 
3459   
3460          # Run the analysis. 
3461          relax_disp.Relax_disp(pipe_name=pipe_name, pipe_bundle=pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, exp_mc_sim_num=EXP_MC_NUM, modsel=MODSEL, r1_fit=r1_fit) 
3462   
3463          # Verify the data. 
3464          self.verify_r1rho_kjaergaard_missing_r1(models=MODELS, result_dir_name=result_dir_name, r2eff_estimate='direct') 
3465   
3466   
3467 -    def test_estimate_r2eff_err_methods(self): 
3468          """Test the user function for estimating R2eff and associated errors for exponential curve fitting with different methods. 
3469          This is compared with a run where erros are estimated by 2000 Monte Carlo simulations. 
3470   
3471          This follows Task 7822. 
3472          U{task #7822<https://gna.org/task/index.php?7822>}: Implement user function to estimate R2eff and associated errors for exponential curve fitting. 
3473   
3474          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
3475          Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
3476   
3477          NOTE: The difference in the methods was due to a bug in relax! 
3478          U{bug #22554<https://gna.org/bugs/index.php?22554>}. The distribution of intensity with errors in Monte-Carlo simulations are markedly more narrow than expected. 
3479   
3480          This dataset is old, and includes 2000 Monte-Carlo simulations, which is performed wrong. 
3481          """ 
3482   
3483          # Define data path. 
3484          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' +sep+ "check_graphs" +sep+ "mc_2000"  +sep+ "R2eff" 
3485   
3486          # Create pipe. 
3487          self.interpreter.pipe.create('MC_2000', 'relax_disp') 
3488   
3489          # Read results for 2000 MC simulations. 
3490          self.interpreter.results.read(prev_data_path + sep + 'results') 
3491   
3492          # Start dic. 
3493          my_dic = {} 
3494          param_key_list = [] 
3495   
3496          # Do boot strapping ? 
3497          do_boot = True 
3498          if do_boot: 
3499              min_algor = 'Newton' 
3500              min_options = () 
3501              sim_boot = 200 
3502              scaling_list = [1.0, 1.0] 
3503   
3504          # First check sim values. 
3505          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3506              # Add key to dic. 
3507              my_dic[spin_id] = {} 
3508   
3509              # Loop over sim. 
3510              for i, r2eff_sim in enumerate(cur_spin.r2eff_sim): 
3511                  # Loop over all exp type. 
3512                  for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
3513                      # Generate the param_key. 
3514                      param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
3515                      r2eff_sim_point = r2eff_sim[param_key] 
3516                      i0_sim_point = cur_spin.r2eff_sim[i][param_key] 
3517   
3518                      # Assert point are higher than 0.0. 
3519                      #point_info = "r2eff=%3.2f i0=%3.2f, at %3.1f MHz, for offset=%3.3f ppm and dispersion point %-5.1f, at sim index %i." % (r2eff_sim_point, i0_sim_point, frq/1E6, offset, point, i) 
3520                      #print(point_info) 
3521                      self.assert_(r2eff_sim_point > 0.0) 
3522                      self.assert_(i0_sim_point > 0.0) 
3523   
3524          # Get the data. 
3525          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3526              # Generate spin string. 
3527              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
3528   
3529              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
3530                  # Generate the param_key. 
3531                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
3532   
3533                  # Loop over all sim, and collect data. 
3534                  r2eff_sim_l = [] 
3535                  i0_sim_l = [] 
3536                  for i, r2eff_sim in enumerate(cur_spin.r2eff_sim): 
3537                      i0_sim = cur_spin.i0_sim[i] 
3538   
3539                      r2eff_sim_i = r2eff_sim[param_key] 
3540                      r2eff_sim_l.append(r2eff_sim_i) 
3541                      i0_sim_i = i0_sim[param_key] 
3542                      i0_sim_l.append(i0_sim_i) 
3543   
3544                  # Take the standard deviation of all values. 
3545                  r2eff_sim_err = std(asarray(r2eff_sim_l), ddof=1) 
3546                  i0_sim_err = std(asarray(i0_sim_l), ddof=1) 
3547   
3548                  # Append key. 
3549                  param_key_list.append(param_key) 
3550   
3551                  # Add key to dic. 
3552                  my_dic[spin_id][param_key] = {} 
3553   
3554                  # Get the value. 
3555                  r2eff = getattr(cur_spin, 'r2eff')[param_key] 
3556                  r2eff_err = getattr(cur_spin, 'r2eff_err')[param_key] 
3557                  i0 = getattr(cur_spin, 'i0')[param_key] 
3558                  i0_err = getattr(cur_spin, 'i0_err')[param_key] 
3559   
3560                  # Save to dic. 
3561                  my_dic[spin_id][param_key]['r2eff'] = r2eff 
3562                  my_dic[spin_id][param_key]['r2eff_err'] = r2eff_err 
3563                  my_dic[spin_id][param_key]['i0'] = i0 
3564                  my_dic[spin_id][param_key]['i0_err'] = i0_err 
3565                  my_dic[spin_id][param_key]['r2eff_err_sim'] = r2eff_sim_err 
3566                  my_dic[spin_id][param_key]['i0_err_sim'] = i0_sim_err 
3567   
3568                  # Assert values are equal 
3569                  self.assertAlmostEqual(r2eff_sim_err, r2eff_err) 
3570                  self.assertAlmostEqual(i0_sim_err, i0_err) 
3571   
3572                  if do_boot: 
3573                      values = [] 
3574                      errors = [] 
3575                      times = [] 
3576                      for time in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point): 
3577                          values.append(average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time)) 
3578                          errors.append(average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, error=True)) 
3579                          times.append(time) 
3580   
3581                      # Convert to numpy array. 
3582                      values = asarray(values) 
3583                      errors = asarray(errors) 
3584                      times = asarray(times) 
3585   
3586                      R_m_sim_l = [] 
3587                      I0_m_sim_l = [] 
3588                      for j in range(sim_boot): 
3589                          if j in range(0, 100000, 100): 
3590                              print("Simulation %i"%j) 
3591                          # Start minimisation. 
3592   
3593                          # Produce errors 
3594                          I_err = [] 
3595                          for j, error in enumerate(errors): 
3596                              I_error = gauss(values[j], error) 
3597                              I_err.append(I_error) 
3598                          # Convert to numpy array. 
3599                          I_err = asarray(I_err) 
3600   
3601                          x0 = [r2eff, i0] 
3602                          setup(num_params=len(x0), num_times=len(times), values=I_err, sd=errors, relax_times=times, scaling_matrix=scaling_list) 
3603   
3604                          params_minfx_sim_j, chi2_minfx_sim_j, iter_count, f_count, g_count, h_count, warning = generic_minimise(func=func, dfunc=dfunc, d2func=d2func, args=(), x0=x0, min_algor=min_algor, min_options=min_options, full_output=True, print_flag=0) 
3605                          R_m_sim_j, I0_m_sim_j = params_minfx_sim_j 
3606                          R_m_sim_l.append(R_m_sim_j) 
3607                          I0_m_sim_l.append(I0_m_sim_j) 
3608   
3609                      # Get stats on distribution. 
3610                      sigma_R_sim = std(asarray(R_m_sim_l), ddof=1) 
3611                      sigma_I0_sim = std(asarray(I0_m_sim_l), ddof=1) 
3612                      my_dic[spin_id][param_key]['r2eff_err_boot'] = sigma_R_sim 
3613                      my_dic[spin_id][param_key]['i0_err_boot'] = sigma_I0_sim 
3614   
3615   
3616          # A new data pipe. 
3617          self.interpreter.pipe.copy(pipe_from='MC_2000', pipe_to='r2eff_est') 
3618          self.interpreter.pipe.switch(pipe_name='r2eff_est') 
3619   
3620          # Delete old errors. 
3621          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3622              delattr(cur_spin, 'r2eff_err') 
3623              delattr(cur_spin, 'i0_err') 
3624   
3625          # Set the model. 
3626          self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
3627   
3628          # Estimate R2eff and errors. 
3629          self.interpreter.relax_disp.r2eff_err_estimate(verbosity=0) 
3630   
3631          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3632              # Generate spin string. 
3633              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
3634   
3635              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
3636                  # Generate the param_key. 
3637                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
3638   
3639                  # Get the value. 
3640                  r2eff_est = getattr(cur_spin, 'r2eff')[param_key] 
3641                  r2eff_err_est = getattr(cur_spin, 'r2eff_err')[param_key] 
3642                  i0_est = getattr(cur_spin, 'i0')[param_key] 
3643                  i0_err_est = getattr(cur_spin, 'i0_err')[param_key] 
3644   
3645                  # Get from dic. 
3646                  r2eff = my_dic[spin_id][param_key]['r2eff'] 
3647                  r2eff_err = my_dic[spin_id][param_key]['r2eff_err'] 
3648                  i0 = my_dic[spin_id][param_key]['i0'] 
3649                  i0_err = my_dic[spin_id][param_key]['i0_err'] 
3650                  r2eff_sim_err = my_dic[spin_id][param_key]['r2eff_err_sim'] 
3651                  i0_sim_err = my_dic[spin_id][param_key]['i0_err_sim'] 
3652   
3653                  if do_boot: 
3654                      r2eff_boot_err = my_dic[spin_id][param_key]['r2eff_err_boot'] 
3655                      i0_boot_err = my_dic[spin_id][param_key]['i0_err_boot'] 
3656                  else: 
3657                      r2eff_boot_err = 0.0 
3658                      i0_boot_err = 0.0 
3659   
3660                  print("%s at %3.1f MHz, for offset=%3.3f ppm and dispersion point %-5.1f." % (exp_type, frq/1E6, offset, point) ) 
3661                  print("r2eff=%3.3f/%3.3f r2eff_err=%3.4f/%3.4f/%3.4f/%3.4f" % (r2eff, r2eff_est, r2eff_err, r2eff_err_est, r2eff_sim_err, r2eff_boot_err) ), 
3662                  print("i0=%3.3f/%3.3f i0_err=%3.4f/%3.4f/%3.4f/%3.4f\n" % (i0, i0_est, i0_err, i0_err_est, i0_sim_err, i0_boot_err) ) 
3663   
3664   
3665          # Now do it manually. 
3666          estimate_r2eff(method='scipy.optimize.leastsq') 
3667   
3668          estimate_r2eff(method='minfx', min_algor='simplex', c_code=True, constraints=False, chi2_jacobian=False) 
3669          estimate_r2eff(method='minfx', min_algor='simplex', c_code=True, constraints=False, chi2_jacobian=True) 
3670   
3671          estimate_r2eff(method='minfx', min_algor='simplex', c_code=False, constraints=False, chi2_jacobian=False) 
3672          estimate_r2eff(method='minfx', min_algor='simplex', c_code=False, constraints=False, chi2_jacobian=True) 
3673   
3674          estimate_r2eff(method='minfx', min_algor='BFGS', c_code=True, constraints=False, chi2_jacobian=False) 
3675          estimate_r2eff(method='minfx', min_algor='BFGS', c_code=True, constraints=False, chi2_jacobian=True) 
3676   
3677          estimate_r2eff(method='minfx', min_algor='BFGS', c_code=False, constraints=False, chi2_jacobian=False) 
3678          estimate_r2eff(method='minfx', min_algor='BFGS', c_code=False, constraints=False, chi2_jacobian=True) 
3679   
3680          estimate_r2eff(method='minfx', min_algor='Newton', c_code=True, constraints=False, chi2_jacobian=False) 
3681          estimate_r2eff(method='minfx', min_algor='Newton', c_code=True, constraints=False, chi2_jacobian=True) 
3682   
3683   
3684   
3685 -    def test_exp_fit(self): 
3686          """Test the relaxation dispersion 'exp_fit' model curve fitting.""" 
3687   
3688          # Execute the script. 
3689          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'exp_fit.py') 
3690   
3691          # The original exponential curve parameters. 
3692          res_data = [ 
3693              [15., 10., 20000., 25000.], 
3694              [12., 11., 50000., 51000.], 
3695              [17., 9., 100000., 96000.] 
3696          ] 
3697   
3698          # List of parameters which do not belong to the model. 
3699          blacklist = ['cpmg_frqs', 'r2', 'rex', 'kex', 'r2a', 'k_AB', 'dw'] 
3700   
3701          # Checks for each residue. 
3702          for i in range(len(res_data)): 
3703              # Printout. 
3704              print("\nResidue number %s." % (i+1)) 
3705   
3706              # Check the fitted parameters. 
3707              self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].r2eff['r1rho_1200.00000000_0.000_1000.000'], res_data[i][0], places=2) 
3708              self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].r2eff['r1rho_1200.00000000_0.000_2000.000'], res_data[i][1], places=2) 
3709              self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].i0['r1rho_1200.00000000_0.000_1000.000']/10000, res_data[i][2]/10000, places=3) 
3710              self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].i0['r1rho_1200.00000000_0.000_2000.000']/10000, res_data[i][3]/10000, places=3) 
3711   
3712              # Check the simulation errors. 
3713              self.assert_(cdp.mol[0].res[i].spin[0].r2eff_err['r1rho_1200.00000000_0.000_1000.000'] < 5.0) 
3714              self.assert_(cdp.mol[0].res[i].spin[0].r2eff_err['r1rho_1200.00000000_0.000_2000.000'] < 5.0) 
3715              self.assert_(cdp.mol[0].res[i].spin[0].i0_err['r1rho_1200.00000000_0.000_1000.000']/10000 < 5.0) 
3716              self.assert_(cdp.mol[0].res[i].spin[0].i0_err['r1rho_1200.00000000_0.000_2000.000']/10000 < 5.0) 
3717   
3718              # Check that certain parameters are not present. 
3719              for param in blacklist: 
3720                  print("\tChecking for the absence of the '%s' parameter." % param) 
3721                  self.assert_(not hasattr(cdp.mol[0].res[i].spin[0], param)) 
3722   
3723          # Check the clustering information. 
3724          self.assert_(hasattr(cdp, 'clustering')) 
3725          keys = ['free spins', 'cluster'] 
3726          for key in keys: 
3727              self.assert_(key in cdp.clustering) 
3728          self.assert_('test' not in cdp.clustering) 
3729          self.assertEqual(cdp.clustering['free spins'], [':2@N']) 
3730          self.assertEqual(cdp.clustering['cluster'], [':1@N', ':3@N']) 
3731   
3732   
3733 -    def test_finite_value(self): 
3734          """Test return from C code, when parameters are wrong.  This can happen, if minfx takes a wrong step.""" 
3735   
3736          times = array([ 0.7,  1.,  0.8,  0.4,  0.9]) 
3737          I = array([ 476.76174875,  372.43328777,  454.20339981,  656.87936253,  419.16726341]) 
3738          errors = array([  9.48032653,  11.34093541,   9.35149017,  10.84867928,  12.17590736]) 
3739   
3740          scaling_list = [1.0, 1.0] 
3741          setup(num_params=2, num_times=len(times), values=I, sd=errors, relax_times=times, scaling_matrix=scaling_list) 
3742   
3743          R = - 500. 
3744          I0 = 1000. 
3745          params = [R, I0] 
3746   
3747          chi2 = func(params) 
3748   
3749          print("The chi2 value returned from C-code for R=%3.2f and I0=%3.2f, then chi2=%3.2f"%(R, I0, chi2)) 
3750          self.assertNotEqual(chi2, inf) 
3751   
3752   
3753 -    def test_hansen_catia_input(self): 
3754          """Conversion of Dr. Flemming Hansen's CPMG R2eff values into input files for CATIA. 
3755   
3756          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
3757          """ 
3758   
3759          # Load the R2eff results file. 
3760          file_name = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen'+sep+'r2eff_pipe' 
3761          self.interpreter.results.read(file_name) 
3762          self.interpreter.deselect.spin(':4') 
3763   
3764          # The spin isotopes. 
3765          self.interpreter.spin.isotope("15N") 
3766   
3767          # Generate the input files. 
3768          self.interpreter.relax_disp.catia_input(dir=ds.tmpdir, force=True) 
3769   
3770          # Check the r2eff set files. 
3771          print("\nChecking the R2eff input set files.") 
3772          files = ['data_set_500.inp', 'data_set_500.inp'] 
3773          for file in files: 
3774              self.assert_(access(ds.tmpdir+sep+file, F_OK)) 
3775          data_set_500 = [ 
3776              "ID=500\n", 
3777              "Sfrq = 500\n", 
3778              "Temperature = 0.0\n", 
3779              "Nucleus = N15\n", 
3780              "Couplednucleus = H1\n", 
3781              "Time_equil = 0.0\n", 
3782              "Pwx_cp = 0.0\n", 
3783              "Taub = 0.0\n", 
3784              "Time_T2 = 0.03\n", 
3785              "Xcar = 0.0\n", 
3786              "Seqfil = CW_CPMG\n", 
3787              "Minerror = (2.%;0.5/s)\n", 
3788              "Basis = (Iph_7)\n", 
3789              "Format = (0;1;2)\n", 
3790              "DataDirectory = /tmp/tmpNjOGNG/input_r2eff\n", 
3791              "Data = (\n", 
3792              " [70N;spin_70_N_500.cpmg];\n", 
3793              " [71N;spin_71_N_500.cpmg];\n", 
3794              ")\n", 
3795          ] 
3796          file = open(ds.tmpdir+sep+files[0]) 
3797          lines = file.readlines() 
3798          file.close() 
3799          for i in range(len(data_set_500)): 
3800              # Skip the data directory, as this is a random file name. 
3801              if i == 14: 
3802                  continue 
3803   
3804              self.assertEqual(data_set_500[i], lines[i]) 
3805   
3806          # Check the r2eff files. 
3807          print("\nChecking the R2eff input files.") 
3808          files = ['spin_70_N_500.cpmg', 'spin_70_N_800.cpmg', 'spin_71_N_500.cpmg', 'spin_71_N_800.cpmg'] 
3809          for file in files: 
3810              self.assert_(access(ds.tmpdir+sep+'input_r2eff'+sep+file, F_OK)) 
3811          spin_70_N_500 = [ 
3812              "#        nu_cpmg(Hz)              R2(1/s)              Esd(R2)\n", 
3813              "  66.666600000000003   16.045540885533605    0.310924686180635\n", 
3814              " 133.333300000000008   14.877924861181727    0.303217270671013\n", 
3815              " 200.000000000000000   14.357820247260586    0.299894424543361\n", 
3816              " 266.666600000000017   12.664494620416516    0.289532060485796\n", 
3817              " 333.333300000000008   12.363204802467891    0.287759631749322\n", 
3818              " 400.000000000000000   11.092532381134513    0.280514035409862\n", 
3819              " 466.666600000000017   10.566090057649893    0.277618625949722\n", 
3820              " 533.333300000000008    9.805806894657803    0.273544382200754\n", 
3821              " 600.000000000000000    9.564300692201730    0.272276309984954\n", 
3822              " 666.666600000000017    9.015633750407980    0.269441511838159\n", 
3823              " 733.333300000000008    8.607764958055581    0.267375134391053\n", 
3824              " 800.000000000000000    8.279997179221338    0.265739551961997\n", 
3825              " 866.666600000000017    8.474535940963516    0.266707642726566\n", 
3826              " 933.333300000000008    8.158972897365194    0.265141210539941\n", 
3827              "1000.000000000000000    7.988630509501972    0.264304105548559\n", 
3828          ] 
3829          file = open(ds.tmpdir+sep+'input_r2eff'+sep+files[0]) 
3830          lines = file.readlines() 
3831          file.close() 
3832          for i in range(len(lines)): 
3833              print("%s\"%s\\n\"," % (" "*12, lines[i][:-1])) 
3834          for i in range(len(spin_70_N_500)): 
3835              self.assertEqual(spin_70_N_500[i], lines[i]) 
3836   
3837          # Check the main file. 
3838          print("\nChecking the main CATIA execution file.") 
3839          main_file = [ 
3840              "ReadDataset(data_set_500.inp)\n", 
3841              "ReadDataset(data_set_800.inp)\n", 
3842              "ReadParam_Global(ParamGlobal.inp)\n", 
3843              "ReadParam_Local(ParamSet1.inp)\n", 
3844              "\n", 
3845              "FreeLocalParam(all;Omega;false)\n", 
3846              "FreeLocalParam(all;R1iph_500;false)\n", 
3847              "FreeLocalParam(all;R1iph_800;false)\n", 
3848              "\n", 
3849              "Minimize(print=y;tol=1e-25;maxiter=10000000)\n", 
3850              "\n", 
3851              "PrintParam(output/GlobalParam.fit;global)\n", 
3852              "PrintParam(output/DeltaOmega.fit;DeltaO)\n", 
3853              "PrintData(output/)\n", 
3854              "\n", 
3855              "ChiSq(all;all)\n", 
3856              "exit(0)\n" 
3857          ] 
3858          file = open("%s%sFit.catia" % (ds.tmpdir, sep)) 
3859          lines = file.readlines() 
3860          file.close() 
3861          for i in range(len(main_file)): 
3862              self.assertEqual(main_file[i], lines[i]) 
3863   
3864   
3865 -    def test_hansen_cpmg_data_auto_analysis(self): 
3866          """Test of the dispersion auto-analysis using Dr. Flemming Hansen's CPMG data. 
3867   
3868          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
3869          """ 
3870   
3871          # Set the model. 
3872          ds.models = [ 
3873              MODEL_NOREX, 
3874              MODEL_LM63, 
3875              MODEL_CR72, 
3876              MODEL_IT99 
3877          ] 
3878   
3879          # Execute the script. 
3880          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_data.py') 
3881          self.interpreter.state.save('analysis_heights', dir=ds.tmpdir, force=True) 
3882   
3883          # The R20 keys. 
3884          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
3885          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
3886   
3887          # The 'No Rex' model checks. 
3888          self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 
3889          spin70 = return_spin(":70") 
3890          spin71 = return_spin(":71") 
3891          print("\n\nOptimised parameters:\n") 
3892          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
3893          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
3894          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
3895          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
3896          self.assertAlmostEqual(spin70.r2[r20_key1], 10.5340593984683, 3) 
3897          self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112170102734, 3) 
3898          self.assertAlmostEqual(spin70.chi2, 8973.84810025761, 3) 
3899          self.assertAlmostEqual(spin71.r2[r20_key1], 5.83139953954648, 3) 
3900          self.assertAlmostEqual(spin71.r2[r20_key2], 8.90856319376098, 3) 
3901          self.assertAlmostEqual(spin71.chi2, 3908.00127830003, 3) 
3902   
3903          # The 'LM63' model checks. 
3904          self.interpreter.pipe.switch(pipe_name='LM63 - relax_disp') 
3905          spin70 = return_spin(":70") 
3906          spin71 = return_spin(":71") 
3907          print("\n\nOptimised parameters:\n") 
3908          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
3909          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
3910          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
3911          print("%-20s %20.15g %20.15g" % ("phi_ex", spin70.phi_ex, spin71.phi_ex)) 
3912          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
3913          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
3914          self.assertAlmostEqual(spin70.r2[r20_key1], 6.74326615264889, 2) 
3915          self.assertAlmostEqual(spin70.r2[r20_key2], 6.57331164382438, 2) 
3916          self.assertAlmostEqual(spin70.phi_ex, 0.312767653822936, 3) 
3917          self.assertAlmostEqual(spin70.kex/10000, 4723.44390412119/10000, 3) 
3918          self.assertAlmostEqual(spin70.chi2, 363.534049046805, 3) 
3919          self.assertAlmostEqual(spin71.r2[r20_key1], 5.00778024769786, 3) 
3920          self.assertAlmostEqual(spin71.r2[r20_key2], 6.83343630016037, 3) 
3921          self.assertAlmostEqual(spin71.phi_ex, 0.0553791362097596, 3) 
3922          self.assertAlmostEqual(spin71.kex/10000, 2781.67925957068/10000, 3) 
3923          self.assertAlmostEqual(spin71.chi2, 17.0776426190574, 3) 
3924   
3925          # The 'CR72' model checks. 
3926          self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 
3927          spin70 = return_spin(":70") 
3928          spin71 = return_spin(":71") 
3929          print("\n\nOptimised parameters:\n") 
3930          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
3931          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
3932          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
3933          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
3934          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
3935          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
3936          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
3937          self.assertAlmostEqual(spin70.r2[r20_key1], 6.97233943292193, 3) 
3938          self.assertAlmostEqual(spin70.r2[r20_key2], 9.409506394526, 2) 
3939          self.assertAlmostEqual(spin70.pA, 0.989856804525044, 3) 
3940          self.assertAlmostEqual(spin70.dw, 5.60889078920945, 3) 
3941          self.assertAlmostEqual(spin70.kex/10000, 1753.01607073019/10000, 3) 
3942          self.assertAlmostEqual(spin70.chi2, 53.8382158551706, 3) 
3943          self.assertAlmostEqual(spin71.r2[r20_key1], 5.003171547206, 3) 
3944          self.assertAlmostEqual(spin71.r2[r20_key2], 6.90210797727492, 3) 
3945          self.assertAlmostEqual(spin71.pA, 0.985922406455826, 3) 
3946          self.assertAlmostEqual(spin71.dw, 2.00500965892672, 2) 
3947          self.assertAlmostEqual(spin71.kex/10000, 2481.10839579617/10000, 3) 
3948          self.assertAlmostEqual(spin71.chi2, 15.6595374286822, 3) 
3949   
3950   
3951 -    def test_hansen_cpmg_data_auto_analysis_numeric(self): 
3952          """Test of the numeric model only dispersion auto-analysis using Dr. Flemming Hansen's CPMG data. 
3953   
3954          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
3955          """ 
3956   
3957          # Set the model and numeric flag. 
3958          ds.models = [ 
3959              MODEL_NOREX, 
3960              MODEL_CR72, 
3961              MODEL_NS_CPMG_2SITE_EXPANDED 
3962          ] 
3963          ds.numeric_only = True 
3964   
3965          # Execute the script. 
3966          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_data.py') 
3967   
3968          # The R20 keys. 
3969          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
3970          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
3971   
3972          # The 'No Rex' model checks. 
3973          self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 
3974          spin70 = return_spin(":70") 
3975          spin71 = return_spin(":71") 
3976          print("\n\nOptimised parameters:\n") 
3977          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
3978          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
3979          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
3980          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
3981          self.assertAlmostEqual(spin70.r2[r20_key1], 10.5340593984683, 3) 
3982          self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112170102734, 3) 
3983          self.assertAlmostEqual(spin70.chi2/10000, 8973.84810025761/10000, 3) 
3984          self.assertAlmostEqual(spin71.r2[r20_key1], 5.83139953954648, 3) 
3985          self.assertAlmostEqual(spin71.r2[r20_key2], 8.90856319376098, 3) 
3986          self.assertAlmostEqual(spin71.chi2/10000, 3908.00127830003/10000, 3) 
3987   
3988          # The 'CR72' model checks. 
3989          self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 
3990          spin70 = return_spin(":70") 
3991          spin71 = return_spin(":71") 
3992          print("\n\nOptimised parameters:\n") 
3993          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
3994          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
3995          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
3996          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
3997          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
3998          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
3999          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4000          self.assertAlmostEqual(spin70.r2[r20_key1], 6.97233943292193, 3) 
4001          self.assertAlmostEqual(spin70.r2[r20_key2], 9.409506394526, 2) 
4002          self.assertAlmostEqual(spin70.pA, 0.989856804525044, 3) 
4003          self.assertAlmostEqual(spin70.dw, 5.60889078920945, 3) 
4004          self.assertAlmostEqual(spin70.kex/10000, 1753.01607073019/10000, 3) 
4005          self.assertAlmostEqual(spin70.chi2, 53.8382158551706, 3) 
4006          self.assertAlmostEqual(spin71.r2[r20_key1], 5.003171547206, 3) 
4007          self.assertAlmostEqual(spin71.r2[r20_key2], 6.90210797727492, 3) 
4008          self.assertAlmostEqual(spin71.pA, 0.985922406455826, 3) 
4009          self.assertAlmostEqual(spin71.dw, 2.00500965892672, 2) 
4010          self.assertAlmostEqual(spin71.kex/10000, 2481.10839579617/10000, 3) 
4011          self.assertAlmostEqual(spin71.chi2, 15.6595374286822, 3) 
4012   
4013          # The 'NS CPMG 2-site expanded' model checks. 
4014          self.interpreter.pipe.switch(pipe_name='NS CPMG 2-site expanded - relax_disp') 
4015          spin70 = return_spin(":70") 
4016          spin71 = return_spin(":71") 
4017          print("\n\nOptimised parameters:\n") 
4018          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4019          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4020          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4021          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4022          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4023          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4024          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4025          self.assertAlmostEqual(spin70.r2[r20_key1], 6.95815351460902, 3) 
4026          self.assertAlmostEqual(spin70.r2[r20_key2], 9.39649535771294, 3) 
4027          self.assertAlmostEqual(spin70.pA, 0.989701014493195, 3) 
4028          self.assertAlmostEqual(spin70.dw, 5.67314464776128, 3) 
4029          self.assertAlmostEqual(spin70.kex/10000, 1713.65380495429/10000, 3) 
4030          self.assertAlmostEqual(spin70.chi2, 52.5106880917473, 3) 
4031          self.assertAlmostEqual(spin71.r2[r20_key1], 4.99889337382435, 3) 
4032          self.assertAlmostEqual(spin71.r2[r20_key2], 6.89822887466673, 3) 
4033          self.assertAlmostEqual(spin71.pA, 0.986709050819695, 3) 
4034          self.assertAlmostEqual(spin71.dw, 2.09238266766502, 2) 
4035          self.assertAlmostEqual(spin71.kex/10000, 2438.27019901422/10000, 3) 
4036          self.assertAlmostEqual(spin71.chi2, 15.1644906963987, 3) 
4037   
4038          # The final data pipe checks. 
4039          self.interpreter.pipe.switch(pipe_name='final - relax_disp') 
4040          spin70 = return_spin(":70") 
4041          spin71 = return_spin(":71") 
4042          self.assertEqual(spin70.model, 'NS CPMG 2-site expanded') 
4043          self.assertEqual(spin71.model, 'NS CPMG 2-site expanded') 
4044   
4045   
4046 -    def test_hansen_cpmg_data_auto_analysis_r2eff(self): 
4047          """Test of the dispersion auto-analysis using Dr. Flemming Hansen's CPMG data (using the R2eff data directly instead of peak intensities). 
4048   
4049          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4050          """ 
4051   
4052          # Set the model. 
4053          ds.models = [ 
4054              MODEL_NOREX, 
4055              MODEL_LM63, 
4056              MODEL_CR72, 
4057              MODEL_IT99 
4058          ] 
4059   
4060          # Execute the script. 
4061          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_r2eff_data.py') 
4062          self.interpreter.state.save('analysis_r2eff', dir=ds.tmpdir, force=True) 
4063   
4064          # The R20 keys. 
4065          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4066          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4067   
4068          # The 'No Rex' model checks. 
4069          self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 
4070          spin70 = return_spin(":70") 
4071          spin71 = return_spin(":71") 
4072          print("\n\nOptimised parameters:\n") 
4073          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4074          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4075          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4076          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4077          self.assertAlmostEqual(spin70.r2[r20_key1], 10.5340593984683, 3) 
4078          self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112170102734, 3) 
4079          self.assertAlmostEqual(spin70.chi2, 8973.84810025761, 3) 
4080          self.assertAlmostEqual(spin71.r2[r20_key1], 5.83139953954648, 3) 
4081          self.assertAlmostEqual(spin71.r2[r20_key2], 8.90856319376098, 3) 
4082          self.assertAlmostEqual(spin71.chi2, 3908.00127830003, 3) 
4083   
4084          # The 'LM63' model checks. 
4085          self.interpreter.pipe.switch(pipe_name='LM63 - relax_disp') 
4086          spin70 = return_spin(":70") 
4087          spin71 = return_spin(":71") 
4088          print("\n\nOptimised parameters:\n") 
4089          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4090          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4091          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4092          print("%-20s %20.15g %20.15g" % ("phi_ex", spin70.phi_ex, spin71.phi_ex)) 
4093          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4094          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4095          self.assertAlmostEqual(spin70.r2[r20_key1], 6.74326615264889, 2) 
4096          self.assertAlmostEqual(spin70.r2[r20_key2], 6.57331164382438, 2) 
4097          self.assertAlmostEqual(spin70.phi_ex, 0.312767653822936, 3) 
4098          self.assertAlmostEqual(spin70.kex/10000, 4723.44390412119/10000, 3) 
4099          self.assertAlmostEqual(spin70.chi2, 363.534049046805, 3) 
4100          self.assertAlmostEqual(spin71.r2[r20_key1], 5.00778024769786, 3) 
4101          self.assertAlmostEqual(spin71.r2[r20_key2], 6.83343630016037, 3) 
4102          self.assertAlmostEqual(spin71.phi_ex, 0.0553791362097596, 3) 
4103          self.assertAlmostEqual(spin71.kex/10000, 2781.67925957068/10000, 3) 
4104          self.assertAlmostEqual(spin71.chi2, 17.0776426190574, 3) 
4105   
4106          # The 'CR72' model checks. 
4107          self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 
4108          spin70 = return_spin(":70") 
4109          spin71 = return_spin(":71") 
4110          print("\n\nOptimised parameters:\n") 
4111          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4112          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4113          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4114          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4115          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4116          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4117          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4118          self.assertAlmostEqual(spin70.r2[r20_key1], 6.97233943292193, 3) 
4119          self.assertAlmostEqual(spin70.r2[r20_key2], 9.409506394526, 2) 
4120          self.assertAlmostEqual(spin70.pA, 0.989856804525044, 3) 
4121          self.assertAlmostEqual(spin70.dw, 5.60889078920945, 3) 
4122          self.assertAlmostEqual(spin70.kex/10000, 1753.01607073019/10000, 3) 
4123          self.assertAlmostEqual(spin70.chi2, 53.8382158551706, 3) 
4124          self.assertAlmostEqual(spin71.r2[r20_key1], 5.00317154730225, 3) 
4125          self.assertAlmostEqual(spin71.r2[r20_key2], 6.90210797713541, 3) 
4126          self.assertAlmostEqual(spin71.pA, 0.985922406429147, 3) 
4127          self.assertAlmostEqual(spin71.dw, 2.00500965887772, 2) 
4128          self.assertAlmostEqual(spin71.kex/10000, 2481.10839579804/10000, 3) 
4129          self.assertAlmostEqual(spin71.chi2, 15.6595374288635, 3) 
4130   
4131   
4132 -    def test_hansen_cpmg_data_missing_auto_analysis(self): 
4133          """Test of the dispersion auto-analysis using Dr. Flemming Hansen's CPMG data with parts missing. 
4134   
4135          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4136          """ 
4137   
4138          # Set the model. 
4139          ds.models = [ 
4140              MODEL_R2EFF, 
4141              MODEL_NOREX, 
4142              MODEL_CR72, 
4143              MODEL_NS_CPMG_2SITE_EXPANDED 
4144          ] 
4145   
4146          # Execute the script. 
4147          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_data_missing.py') 
4148          self.interpreter.state.save('analysis_heights', dir=ds.tmpdir, force=True) 
4149   
4150          # The R20 keys. 
4151          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4152          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4153   
4154          # The 'No Rex' model checks. 
4155          self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 
4156          spin4 = return_spin(":4") 
4157          spin70 = return_spin(":70") 
4158          spin71 = return_spin(":71") 
4159          print("\n\nOptimised parameters:\n") 
4160          print("%-20s %-20s %-20s %-20s" % ("Parameter", "Value (:4)", "Value (:70)", "Value (:71)")) 
4161          print("%-20s %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin4.r2[r20_key1], spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4162          print("%-20s %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin4.r2[r20_key2], spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4163          print("%-20s %20.15g %20.15g %20.15g\n" % ("chi2", spin4.chi2, spin70.chi2, spin71.chi2)) 
4164          self.assertAlmostEqual(spin4.r2[r20_key1], 1.60463084515171, 3) 
4165          self.assertAlmostEqual(spin4.r2[r20_key2], 1.63220784651911, 3) 
4166          self.assertAlmostEqual(spin4.chi2, 26.7356700694891, 3) 
4167          self.assertAlmostEqual(spin70.r2[r20_key1], 10.534285641325, 3) 
4168          self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112794857068, 3) 
4169          self.assertAlmostEqual(spin70.chi2, 8973.84809774722, 3) 
4170          self.assertAlmostEqual(spin71.r2[r20_key1], 5.83136858890037, 3) 
4171          self.assertAlmostEqual(spin71.chi2, 182.60081909193, 3) 
4172   
4173          # The 'CR72' model checks. 
4174          self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 
4175          spin4 = return_spin(":4") 
4176          spin70 = return_spin(":70") 
4177          spin71 = return_spin(":71") 
4178          print("\n\nOptimised parameters:\n") 
4179          print("%-20s %-20s %-20s %-20s" % ("Parameter", "Value (:4)", "Value (:70)", "Value (:71)")) 
4180          print("%-20s %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin4.r2[r20_key1], spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4181          print("%-20s %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin4.r2[r20_key2], spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4182          print("%-20s %20.15g %20.15g %20.15g" % ("pA", spin4.pA, spin70.pA, spin71.pA)) 
4183          print("%-20s %20.15g %20.15g %20.15g" % ("dw", spin4.dw, spin70.dw, spin71.dw)) 
4184          print("%-20s %20.15g %20.15g %20.15g" % ("kex", spin4.kex, spin70.kex, spin71.kex)) 
4185          print("%-20s %20.15g %20.15g %20.15g\n" % ("chi2", spin4.chi2, spin70.chi2, spin71.chi2)) 
4186          self.assertAlmostEqual(spin4.r2[r20_key1], 1.60463650370664, 2) 
4187          self.assertAlmostEqual(spin4.r2[r20_key2], 1.63221675941434, 3) 
4188          #self.assertAlmostEqual(spin4.pA, 0.818979078699935, 3)    # As dw (and kex) is zero, this parameter is not stable. 
4189          self.assertAlmostEqual(spin4.dw, 0.0, 2) 
4190          self.assertAlmostEqual(spin4.kex/10000, 0.0, 3) 
4191          self.assertAlmostEqual(spin4.chi2/100, 26.7356711142038/100, 3) 
4192          self.assertAlmostEqual(spin70.r2[r20_key1], 6.97268077496405, 3) 
4193          self.assertAlmostEqual(spin70.r2[r20_key2], 9.41028133407727, 3) 
4194          self.assertAlmostEqual(spin70.pA, 0.989856641885939, 3) 
4195          self.assertAlmostEqual(spin70.dw, 5.60889911049405, 3) 
4196          self.assertAlmostEqual(spin70.kex/10000, 1752.62025618632/10000, 3) 
4197          self.assertAlmostEqual(spin70.chi2, 53.8382196964083, 3) 
4198          self.assertAlmostEqual(spin71.r2[r20_key1], 4.98123328466942, 3) 
4199          self.assertAlmostEqual(spin71.pA, 0.996607425484157, 3) 
4200          self.assertAlmostEqual(spin71.dw, 4.34346257383825, 2) 
4201          self.assertAlmostEqual(spin71.kex/10000, 1936.73197158804/10000, 3) 
4202          self.assertAlmostEqual(spin71.chi2, 5.51703791653689, 3) 
4203   
4204   
4205 -    def test_hansen_cpmg_data_to_cr72(self): 
4206          """Optimisation of Dr. Flemming Hansen's CPMG data to the CR72 dispersion model. 
4207   
4208          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4209          """ 
4210   
4211          # Base data setup. 
4212          self.setup_hansen_cpmg_data(model='CR72') 
4213   
4214          # Alias the spins. 
4215          spin70 = return_spin(":70") 
4216          spin71 = return_spin(":71") 
4217   
4218          # The R20 keys. 
4219          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4220          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4221   
4222          # Set the initial parameter values. 
4223          spin70.r2 = {r20_key1: 7.0, r20_key2: 9.0} 
4224          spin70.pA = 0.9 
4225          spin70.dw = 6.0 
4226          spin70.kex = 1500.0 
4227          spin71.r2 = {r20_key1: 5, r20_key2: 9.0} 
4228          spin71.pA = 0.9 
4229          spin71.dw = 4.0 
4230          spin71.kex = 1900.0 
4231   
4232          # Low precision optimisation. 
4233          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
4234   
4235          # Printout. 
4236          print("\n\nOptimised parameters:\n") 
4237          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4238          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4239          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4240          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4241          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4242          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4243          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4244   
4245          # Checks for residue :70. 
4246          self.assertAlmostEqual(spin70.r2[r20_key1], 6.9724581325007, 4) 
4247          self.assertAlmostEqual(spin70.r2[r20_key2], 9.40968331038162, 2) 
4248          self.assertAlmostEqual(spin70.pA, 0.989856656702431, 4) 
4249          self.assertAlmostEqual(spin70.dw, 5.60885879594746, 3) 
4250          self.assertAlmostEqual(spin70.kex/1000, 1752.91052702273/1000, 3) 
4251          self.assertAlmostEqual(spin70.chi2, 53.8382133597495, 4) 
4252   
4253          # Checks for residue :71. 
4254          self.assertAlmostEqual(spin71.r2[r20_key1], 5.0030740940524, 4) 
4255          self.assertAlmostEqual(spin71.pA, 0.985941082507823, 4) 
4256          self.assertAlmostEqual(spin71.dw, 2.00640384113696, 4) 
4257          self.assertAlmostEqual(spin71.kex/1000, 2480.79614442041/1000, 4) 
4258          self.assertAlmostEqual(spin71.chi2, 15.6595388312451, 4) 
4259   
4260          # Test the conversion to k_AB from kex and pA. 
4261          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4262          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4263   
4264          # Test the conversion to k_BA from kex and pA. 
4265          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4266          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4267   
4268   
4269 -    def test_hansen_cpmg_data_to_cr72_full(self): 
4270          """Optimisation of Dr. Flemming Hansen's CPMG data to the CR72 full dispersion model. 
4271   
4272          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4273          """ 
4274   
4275          # Base data setup. 
4276          self.setup_hansen_cpmg_data(model='CR72 full') 
4277   
4278          # Alias the spins. 
4279          spin70 = return_spin(":70") 
4280          spin71 = return_spin(":71") 
4281   
4282          # The R20 keys. 
4283          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4284          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4285   
4286          # Set the initial parameter values. 
4287          spin70.r2a = {r20_key1: 7.0, r20_key2: 9.0} 
4288          spin70.r2b = {r20_key1: 7.0, r20_key2: 9.0} 
4289          spin70.pA = 0.9 
4290          spin70.dw = 6.0 
4291          spin70.kex = 1500.0 
4292          spin71.r2a = {r20_key1: 5.0, r20_key2: 9.0} 
4293          spin71.r2b = {r20_key1: 5.0, r20_key2: 9.0} 
4294          spin71.pA = 0.9 
4295          spin71.dw = 4.0 
4296          spin71.kex = 1900.0 
4297   
4298          # Low precision optimisation. 
4299          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
4300   
4301          # Printout. 
4302          print("\n\nOptimised parameters:\n") 
4303          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4304          print("%-20s %20.15g %20.15g" % ("R2A (500 MHz)", spin70.r2a[r20_key1], spin71.r2a[r20_key1])) 
4305          print("%-20s %20.15g %20.15g" % ("R2B (500 MHz)", spin70.r2b[r20_key1], spin71.r2b[r20_key1])) 
4306          print("%-20s %20.15g %20.15g" % ("R2A (800 MHz)", spin70.r2a[r20_key2], spin71.r2a[r20_key2])) 
4307          print("%-20s %20.15g %20.15g" % ("R2B (800 MHz)", spin70.r2b[r20_key2], spin71.r2b[r20_key2])) 
4308          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4309          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4310          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4311          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4312   
4313          # Checks for residue :70. 
4314          self.assertAlmostEqual(spin70.r2a[r20_key1], 6.87485258365614, 4) 
4315          self.assertAlmostEqual(spin70.r2b[r20_key1], 1.26075839074614, 4) 
4316          self.assertAlmostEqual(spin70.r2a[r20_key2], 8.79580446260797, 4) 
4317          self.assertAlmostEqual(spin70.r2b[r20_key2], 51.188411562843, 4) 
4318          self.assertAlmostEqual(spin70.pA, 0.989384178573802, 4) 
4319          self.assertAlmostEqual(spin70.dw, 5.54738203723682, 4) 
4320          self.assertAlmostEqual(spin70.kex/1000, 1831.4566463179/1000, 4) 
4321          self.assertAlmostEqual(spin70.chi2, 50.450410782403, 4) 
4322   
4323          # Checks for residue :71. 
4324          self.assertAlmostEqual(spin71.r2a[r20_key1], 5.04185695754972, 4) 
4325          self.assertAlmostEqual(spin71.r2b[r20_key1], 1.62857899941921, 4) 
4326          self.assertAlmostEqual(spin71.pA, 0.988832866751676, 4) 
4327          self.assertAlmostEqual(spin71.dw, 2.24905251856265, 4) 
4328          self.assertAlmostEqual(spin71.kex/1000, 2397.64122642946/1000, 4) 
4329          self.assertAlmostEqual(spin71.chi2, 15.8586492923672, 4) 
4330   
4331          # Test the conversion to k_AB from kex and pA. 
4332          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4333          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4334   
4335          # Test the conversion to k_BA from kex and pA. 
4336          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4337          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4338   
4339   
4340 -    def test_hansen_cpmg_data_to_it99(self): 
4341          """Optimisation of Dr. Flemming Hansen's CPMG data to the IT99 dispersion model. 
4342   
4343          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4344          """ 
4345   
4346          # Base data setup. 
4347          self.setup_hansen_cpmg_data(model='IT99') 
4348   
4349          # Alias the spins. 
4350          spin70 = return_spin(":70") 
4351          spin71 = return_spin(":71") 
4352   
4353          # The R20 keys. 
4354          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4355          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4356   
4357          # Set the initial parameter values. 
4358          spin70.r2 = {r20_key1: 8.8, r20_key2: 16.6} 
4359          spin70.dw = 10.0 
4360          spin70.pA = 0.5 
4361          spin70.tex = 1000.09 
4362          spin71.r2 = {r20_key1: 1.0, r20_key2: 1.0} 
4363          spin71.dw = 10.0 
4364          spin71.pA = 0.95 
4365          spin71.tex = 0.1 
4366   
4367          # Low precision optimisation. 
4368          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-10, grad_tol=None, max_iter=10000, constraints=True, scaling=True, verbosity=1) 
4369   
4370          # Printout. 
4371          print("\n\nOptimised parameters:\n") 
4372          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4373          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4374          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4375          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4376          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4377          print("%-20s %20.15g %20.15g" % ("tex", spin70.tex, spin71.tex)) 
4378          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4379   
4380          # Checks for residue :70. 
4381          self.assertAlmostEqual(spin70.r2[r20_key1], 7.24471197811838, 4) 
4382          self.assertAlmostEqual(spin70.r2[r20_key2], 10.0571040704729, 4) 
4383          self.assertAlmostEqual(spin70.dw, 5.2116923222744, 4) 
4384          self.assertAlmostEqual(spin70.pA, 0.990253627907212, 4) 
4385          self.assertAlmostEqual(spin70.tex*1000, 0.000638394793480444*1000, 4) 
4386          self.assertAlmostEqual(spin70.chi2, 93.5135798618747, 4) 
4387   
4388          # Checks for residue :71. 
4389          self.assertAlmostEqual(spin71.r2[r20_key1], 5.05971235970214, 4) 
4390          self.assertAlmostEqual(spin71.r2[r20_key2], 6.96641194493447, 4) 
4391          self.assertAlmostEqual(spin71.dw, 0.435389946897141, 4) 
4392          self.assertAlmostEqual(spin71.pA, 0.500000000213519, 3) 
4393          self.assertAlmostEqual(spin71.tex*1000, 0.000372436400585538*1000, 4) 
4394          self.assertAlmostEqual(spin71.chi2, 23.7895798801404, 4) 
4395   
4396   
4397 -    def test_hansen_cpmg_data_to_lm63(self): 
4398          """Optimisation of Dr. Flemming Hansen's CPMG data to the LM63 dispersion model. 
4399   
4400          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4401          """ 
4402   
4403          # Base data setup. 
4404          self.setup_hansen_cpmg_data(model='LM63') 
4405   
4406          # Alias the spins. 
4407          spin70 = return_spin(":70") 
4408          spin71 = return_spin(":71") 
4409   
4410          # The R20 keys. 
4411          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4412          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4413   
4414          # Set the initial parameter values. 
4415          spin70.r2 = {r20_key1: 7.0, r20_key2: 7.0} 
4416          spin70.phi_ex = 0.3 
4417          spin70.kex = 5000.0 
4418          spin71.r2 = {r20_key1: 5.0, r20_key2: 9.0} 
4419          spin71.phi_ex = 0.1 
4420          spin71.kex = 2500.0 
4421   
4422          # Low precision optimisation. 
4423          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-25, grad_tol=None, max_iter=10000000, constraints=True, scaling=True, verbosity=1) 
4424   
4425          # Printout. 
4426          print("\n\nOptimised parameters:\n") 
4427          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4428          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4429          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4430          print("%-20s %20.15g %20.15g" % ("phi_ex", spin70.phi_ex, spin71.phi_ex)) 
4431          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4432          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4433   
4434          # Checks for residue :70. 
4435          self.assertAlmostEqual(spin70.r2[r20_key1], 6.74362294539099) 
4436          self.assertAlmostEqual(spin70.r2[r20_key2], 6.57406797067481, 6) 
4437          self.assertAlmostEqual(spin70.phi_ex, 0.312733013751449) 
4438          self.assertAlmostEqual(spin70.kex/1000, 4723.09897146338/1000, 6) 
4439          self.assertAlmostEqual(spin70.chi2, 363.534044873483) 
4440   
4441          # Checks for residue :71. 
4442          self.assertAlmostEqual(spin71.r2[r20_key1], 5.00776657729728, 5) 
4443          self.assertAlmostEqual(spin71.phi_ex, 0.0553787825650613, 5) 
4444          self.assertAlmostEqual(spin71.kex/1000, 2781.72292994154/1000, 5) 
4445          self.assertAlmostEqual(spin71.chi2, 17.0776399916287, 5) 
4446   
4447   
4448 -    def test_hansen_cpmg_data_to_lm63_3site(self): 
4449          """Optimisation of Dr. Flemming Hansen's CPMG data to the LM63 dispersion model. 
4450   
4451          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4452          """ 
4453   
4454          # Base data setup. 
4455          self.setup_hansen_cpmg_data(model='LM63 3-site') 
4456   
4457          # Alias the spins. 
4458          spin70 = return_spin(":70") 
4459          spin71 = return_spin(":71") 
4460   
4461          # The R20 keys. 
4462          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4463          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4464   
4465          ## Set the initial parameter values. 
4466          spin70.r2 = {r20_key1: 7.570370921220954, r20_key2: 8.694446951909107} 
4467          spin70.phi_ex_B = 0.14872003058250227 
4468          spin70.phi_ex_C = 0.1319419923472704 
4469          spin70.kB = 4103.672910444741 
4470          spin70.kC = 7029.001690726248 
4471          spin71.r2 = {r20_key1: 5.1347793381636, r20_key2: 7.156573986051575} 
4472          spin71.phi_ex_B = 0.04013553485505605 
4473          spin71.phi_ex_C = 0.020050748406928887 
4474          spin71.kB = 4045.3007136121364 
4475          spin71.kC = 3586.38798270774 
4476   
4477          #self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
4478          #self.interpreter.minimise.grid_search(lower=None, upper=None, inc=41, constraints=True, verbosity=1) 
4479   
4480          # Low precision optimisation. 
4481          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-25, grad_tol=None, max_iter=10000000, constraints=True, scaling=True, verbosity=1) 
4482   
4483          # Printout. 
4484          print("\n\nOptimised parameters:\n") 
4485          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4486          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4487          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4488          print("%-20s %20.15g %20.15g" % ("phi_ex_B", spin70.phi_ex_B, spin71.phi_ex_B)) 
4489          print("%-20s %20.15g %20.15g" % ("phi_ex_C", spin70.phi_ex_C, spin71.phi_ex_C)) 
4490          print("%-20s %20.15g %20.15g" % ("kB", spin70.kB, spin71.kB)) 
4491          print("%-20s %20.15g %20.15g" % ("kC", spin70.kC, spin71.kC)) 
4492          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4493   
4494          # Checks for residue :70. 
4495          self.assertAlmostEqual(spin70.r2[r20_key1], 6.7436230253685, 5) 
4496          self.assertAlmostEqual(spin70.r2[r20_key2], 6.57406813008828, 6) 
4497          self.assertAlmostEqual(spin70.phi_ex_B, 0.206304023079778, 5) 
4498          self.assertAlmostEqual(spin70.phi_ex_C, 0.106428983339627, 5) 
4499          self.assertAlmostEqual(spin70.kB/1000, 4723.09897652589/1000, 6) 
4500          self.assertAlmostEqual(spin70.kC/1000, 4723.09876196409/1000, 6) 
4501          self.assertAlmostEqual(spin70.chi2, 363.534044873483, 5) 
4502   
4503          # Checks for residue :71. 
4504          self.assertAlmostEqual(spin71.r2[r20_key1], 4.96612095596752, 5) 
4505          self.assertAlmostEqual(spin71.phi_ex_B, 0.00398262266512895, 5) 
4506          self.assertAlmostEqual(spin71.phi_ex_C, 0.0555791581291262, 5) 
4507          self.assertAlmostEqual(spin71.kB/1000, 1323.33195689832/1000, 5) 
4508          self.assertAlmostEqual(spin71.kC/1000, 3149.58971568059/1000, 5) 
4509          self.assertAlmostEqual(spin71.chi2, 16.2620934464368) 
4510   
4511   
4512 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_3D(self): 
4513          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site 3D' dispersion model. 
4514   
4515          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4516          """ 
4517   
4518          # Base data setup. 
4519          self.setup_hansen_cpmg_data(model='NS CPMG 2-site 3D') 
4520   
4521          # Alias the spins. 
4522          spin70 = return_spin(":70") 
4523          spin71 = return_spin(":71") 
4524   
4525          # The R20 keys. 
4526          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4527          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4528   
4529          # Set the initial parameter values. 
4530          spin70.r2 = {r20_key1: 6.994165925, r20_key2: 9.428129427} 
4531          spin70.pA = 0.9897754407 
4532          spin70.dw = 5.642418428 
4533          spin70.kex = 1743.666375 
4534          spin71.r2 = {r20_key1: 4.978654237, r20_key2: 9.276918959} 
4535          spin71.pA = 0.9968032899 
4536          spin71.dw = 4.577891393 
4537          spin71.kex = 1830.044597 
4538   
4539          # Low precision optimisation. 
4540          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=False, scaling=True, verbosity=1) 
4541   
4542          # Printout. 
4543          print("\n\nOptimised parameters:\n") 
4544          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4545          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4546          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4547          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4548          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4549          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4550          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4551   
4552          # Checks for residue :70. 
4553          self.assertAlmostEqual(spin70.r2[r20_key1], 6.95797760459016, 4) 
4554          self.assertAlmostEqual(spin70.r2[r20_key2], 9.39628959312699, 4) 
4555          self.assertAlmostEqual(spin70.pA, 0.989700985380975, 4) 
4556          self.assertAlmostEqual(spin70.dw, 5.6733714171086, 4) 
4557          self.assertAlmostEqual(spin70.kex/1000, 1713.63101361545/1000, 4) 
4558          self.assertAlmostEqual(spin70.chi2, 52.5106928523775, 4) 
4559   
4560          # Checks for residue :71. 
4561          self.assertAlmostEqual(spin71.r2[r20_key1], 4.99893565849977, 4) 
4562          self.assertAlmostEqual(spin71.r2[r20_key2], 6.89825625944034, 4) 
4563          self.assertAlmostEqual(spin71.pA, 0.986716058519642, 4) 
4564          self.assertAlmostEqual(spin71.dw, 2.09292495350993, 4) 
4565          self.assertAlmostEqual(spin71.kex/1000, 2438.04423541463/1000, 4) 
4566          self.assertAlmostEqual(spin71.chi2, 15.164490242352, 4) 
4567   
4568          # Test the conversion to k_AB from kex and pA. 
4569          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4570          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4571   
4572          # Test the conversion to k_BA from kex and pA. 
4573          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4574          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4575   
4576   
4577 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_3D_full(self): 
4578          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site 3D full' dispersion model. 
4579   
4580          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4581          """ 
4582   
4583          # Base data setup. 
4584          self.setup_hansen_cpmg_data(model='NS CPMG 2-site 3D full') 
4585   
4586          # Alias the spins. 
4587          spin70 = return_spin(":70") 
4588          spin71 = return_spin(":71") 
4589   
4590          # The R20 keys. 
4591          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4592          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4593   
4594          # Set the initial parameter values. 
4595          spin70.r2a = {r20_key1: 6.644753428, r20_key2: 7.891776687} 
4596          spin70.r2b = {r20_key1: 7.163478485, r20_key2: 138.5170395} 
4597          spin70.pA = 0.9884781357 
4598          spin70.dw = 5.456507396 
4599          spin70.kex = 1906.521189 
4600          spin71.r2a = {r20_key1: 4.99893524108981, r20_key2: 100.0} 
4601          spin71.r2b = {r20_key1: 8.27456243639973, r20_key2: 100.0} 
4602          spin71.pA = 0.986709616684097 
4603          spin71.dw = 2.09245158280905 
4604          spin71.kex = 2438.2766211401 
4605   
4606          # Low precision optimisation. 
4607          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=False, scaling=True, verbosity=1) 
4608   
4609          # Printout. 
4610          print("\n\nOptimised parameters:\n") 
4611          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4612          print("%-20s %20.15g %20.15g" % ("R2A (500 MHz)", spin70.r2a[r20_key1], spin71.r2a[r20_key1])) 
4613          print("%-20s %20.15g %20.15g" % ("R2B (500 MHz)", spin70.r2b[r20_key1], spin71.r2b[r20_key1])) 
4614          print("%-20s %20.15g %20.15g" % ("R2A (800 MHz)", spin70.r2a[r20_key2], spin71.r2a[r20_key2])) 
4615          print("%-20s %20.15g %20.15g" % ("R2B (800 MHz)", spin70.r2b[r20_key2], spin71.r2b[r20_key2])) 
4616          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4617          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4618          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4619          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4620   
4621          # Checks for residue :70. 
4622          self.assertAlmostEqual(spin70.r2a[r20_key1], 6.61176004043484, 4) 
4623          self.assertAlmostEqual(spin70.r2b[r20_key1], 7.4869316381241, 4) 
4624          self.assertAlmostEqual(spin70.r2a[r20_key2], 7.78200386067591, 4) 
4625          self.assertAlmostEqual(spin70.r2b[r20_key2], 141.703593742468, 4) 
4626          self.assertAlmostEqual(spin70.pA, 0.988404987055969, 4) 
4627          self.assertAlmostEqual(spin70.dw, 5.4497360203213, 4) 
4628          self.assertAlmostEqual(spin70.kex/1000, 1934.09304607082/1000, 4) 
4629          self.assertAlmostEqual(spin70.chi2, 44.6793752187925, 4) 
4630   
4631          # Checks for residue :71. 
4632          self.assertAlmostEqual(spin71.r2a[r20_key1], 4.6013095731966, 4) 
4633          self.assertAlmostEqual(spin71.r2b[r20_key1], 13.3245678276332, 4) 
4634          self.assertAlmostEqual(spin71.r2a[r20_key2], 2.08243621257779, 4) 
4635          self.assertAlmostEqual(spin71.r2b[r20_key2], 153.355765094575, 4) 
4636          self.assertAlmostEqual(spin71.pA, 0.9665748685124, 4) 
4637          self.assertAlmostEqual(spin71.dw, 1.41898001408953, 4) 
4638          self.assertAlmostEqual(spin71.kex/1000, 2580.65795560688/1000, 4) 
4639          self.assertAlmostEqual(spin71.chi2, 13.4937006732165, 4) 
4640   
4641          # Test the conversion to k_AB from kex and pA. 
4642          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4643          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4644   
4645          # Test the conversion to k_BA from kex and pA. 
4646          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4647          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4648   
4649   
4650 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_expanded(self): 
4651          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site expanded' dispersion model. 
4652   
4653          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4654          """ 
4655   
4656          # Base data setup. 
4657          self.setup_hansen_cpmg_data(model='NS CPMG 2-site expanded') 
4658   
4659          # Alias the spins. 
4660          spin70 = return_spin(":70") 
4661          spin71 = return_spin(":71") 
4662   
4663          # The R20 keys. 
4664          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4665          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4666   
4667          # Set the initial parameter values. 
4668          spin70.r2 = {r20_key1: 7.0, r20_key2: 9.0} 
4669          spin70.pA = 0.9 
4670          spin70.dw = 6.0 
4671          spin70.kex = 1500.0 
4672          spin71.r2 = {r20_key1: 5.0, r20_key2: 9.0} 
4673          spin71.pA = 0.9 
4674          spin71.dw = 4.0 
4675          spin71.kex = 1900.0 
4676   
4677          # Low precision optimisation. 
4678          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
4679   
4680          # Printout. 
4681          print("\n\nOptimised parameters:\n") 
4682          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4683          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4684          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4685          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4686          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4687          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4688          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4689   
4690          # Checks for residue :70. 
4691          self.assertAlmostEqual(spin70.r2[r20_key1], 6.95813330991529, 4) 
4692          self.assertAlmostEqual(spin70.r2[r20_key2], 9.39663480561524, 4) 
4693          self.assertAlmostEqual(spin70.pA, 0.989700843879574, 4) 
4694          self.assertAlmostEqual(spin70.dw, 5.67315878825691, 4) 
4695          self.assertAlmostEqual(spin70.kex/1000, 1713.56110716632/1000, 4) 
4696          self.assertAlmostEqual(spin70.chi2, 52.5106879242812, 4) 
4697   
4698          # Checks for residue :71. 
4699          self.assertAlmostEqual(spin71.r2[r20_key1], 4.99881666793312, 4) 
4700          self.assertAlmostEqual(spin71.r2[r20_key2], 6.89817482453042, 4) 
4701          self.assertAlmostEqual(spin71.pA, 0.986712911453639, 4) 
4702          self.assertAlmostEqual(spin71.dw, 2.09273069372236, 4) 
4703          self.assertAlmostEqual(spin71.kex/1000, 2438.20525930405/1000, 4) 
4704          self.assertAlmostEqual(spin71.chi2, 15.1644913030633, 4) 
4705   
4706          # Test the conversion to k_AB from kex and pA. 
4707          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4708          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4709   
4710          # Test the conversion to k_BA from kex and pA. 
4711          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4712          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4713   
4714   
4715 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_star(self): 
4716          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site star' dispersion model. 
4717   
4718          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4719          """ 
4720   
4721          # Base data setup. 
4722          self.setup_hansen_cpmg_data(model='NS CPMG 2-site star') 
4723   
4724          # Alias the spins. 
4725          spin70 = return_spin(":70") 
4726          spin71 = return_spin(":71") 
4727   
4728          # The R20 keys. 
4729          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4730          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4731   
4732          # Set the initial parameter values. 
4733          spin70.r2 = {r20_key1: 6.996327746, r20_key2: 9.452051268} 
4734          spin70.pA = 0.9897519798 
4735          spin70.dw = 5.644862195 
4736          spin70.kex = 1723.820567 
4737          spin71.r2 = {r20_key1: 4.978654237, r20_key2: 9.276918959} 
4738          spin71.pA = 0.9968032899 
4739          spin71.dw = 4.577891393 
4740          spin71.kex = 1830.044597 
4741   
4742          # Low precision optimisation. 
4743          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=False, scaling=True, verbosity=1) 
4744   
4745          # Printout. 
4746          print("\n\nOptimised parameters:\n") 
4747          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4748          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4749          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4750          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4751          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4752          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4753          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4754   
4755          # Checks for residue :70. 
4756          self.assertAlmostEqual(spin70.r2[r20_key1], 6.95543947938561, 1) 
4757          self.assertAlmostEqual(spin70.r2[r20_key2], 9.38991914134929, 1) 
4758          self.assertAlmostEqual(spin70.pA, 0.989702750971153, 3) 
4759          self.assertAlmostEqual(spin70.dw, 5.67527122494516, 1) 
4760          self.assertAlmostEqual(spin70.kex/1000, 1715.72032391817/1000, 1) 
4761          self.assertAlmostEqual(spin70.chi2, 52.5011991483842, 1) 
4762   
4763          # Checks for residue :71. 
4764          self.assertAlmostEqual(spin71.r2[r20_key1], 4.992594256544, 1) 
4765          self.assertAlmostEqual(spin71.pA, 0.986716058519642, 2) 
4766          self.assertAlmostEqual(spin71.dw/100, 2.09292495350993/100, 2) 
4767          self.assertAlmostEqual(spin71.kex/100000, 2438.04423541463/100000, 2) 
4768          self.assertAlmostEqual(spin71.chi2/100, 15.1644902423334/100, 1) 
4769   
4770          # Test the conversion to k_AB from kex and pA. 
4771          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4772          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4773   
4774          # Test the conversion to k_BA from kex and pA. 
4775          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4776          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4777   
4778   
4779 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_star_full(self): 
4780          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site star full' dispersion model. 
4781   
4782          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4783          """ 
4784   
4785          # Base data setup. 
4786          self.setup_hansen_cpmg_data(model='NS CPMG 2-site star full') 
4787   
4788          # Alias the spins. 
4789          spin70 = return_spin(":70") 
4790          spin71 = return_spin(":71") 
4791   
4792          # The R20 keys. 
4793          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4794          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4795   
4796          # Set the initial parameter values. 
4797          spin70.r2a = {r20_key1: 6.44836878645126, r20_key2: 7.00382877393494} 
4798          spin70.r2b = {r20_key1: 12.2083127421994, r20_key2: 199.862962628402} 
4799          spin70.pA = 0.987648082613451 
4800          spin70.dw = 5.30679853807572 
4801          spin70.kex = 2033.25380420666 
4802          spin71.r2a = {r20_key1: 4.992594256544, r20_key2: 6.98674718938435} 
4803          spin71.r2b = {r20_key1: 4.992594256544, r20_key2: 6.98674718938435} 
4804          spin71.pA = 0.992258541625787 
4805          spin71.dw = 2.75140650899058 
4806          spin71.kex = 2106.60885247431 
4807   
4808          # Low precision optimisation. 
4809          self.interpreter.minimise.calculate() 
4810   
4811          # Checks for residue :70. 
4812          self.assertAlmostEqual(spin70.chi2/10, 45.773987568491123/10, 2) 
4813          self.assertAlmostEqual(spin71.chi2/10, 17.329385665659192/10, 2) 
4814   
4815   
4816 -    def test_hansen_cpmgfit_input(self): 
4817          """Conversion of Dr. Flemming Hansen's CPMG R2eff values into input files for CPMGFit. 
4818   
4819          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4820          """ 
4821   
4822          # Load the R2eff results file. 
4823          file_name = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen'+sep+'r2eff_pipe' 
4824          self.interpreter.results.read(file_name) 
4825          self.interpreter.deselect.spin(':4') 
4826   
4827          # Set up the model. 
4828          self.interpreter.relax_disp.select_model('LM63') 
4829   
4830          # Generate the input files. 
4831          self.interpreter.relax_disp.cpmgfit_input(force=True, dir=ds.tmpdir) 
4832   
4833          # What the files should contain. 
4834          batch_file = ['#! /bin/sh\n', '\n', 'cpmgfit -grid -xmgr -f spin_70_N.in | tee spin_70_N.out\n', 'cpmgfit -grid -xmgr -f spin_71_N.in | tee spin_71_N.out\n'] 
4835          spin1 = [ 
4836              "title :70@N\n", 
4837              "fields 2 11.7432964915 18.7892743865\n", 
4838              "function CPMG\n", 
4839              "R2 1 10 20\n", 
4840              "Rex 0 100.0 100\n", 
4841              "Tau 0 10.0 100\n", 
4842              "xmgr\n", 
4843              "@ xaxis label \"1/tcp (1/ms)\"\n", 
4844              "@ yaxis label \"R2(tcp) (rad/s)\"\n", 
4845              "@ xaxis ticklabel format decimal\n", 
4846              "@ yaxis ticklabel format decimal\n", 
4847              "@ xaxis ticklabel char size 0.8\n", 
4848              "@ yaxis ticklabel char size 0.8\n", 
4849              "@ world xmin 0.0\n", 
4850              "data\n", 
4851              "0.133333             16.045541            0.310925             11.743296           \n", 
4852              "0.266667             14.877925            0.303217             11.743296           \n", 
4853              "0.400000             14.357820            0.299894             11.743296           \n", 
4854              "0.533333             12.664495            0.289532             11.743296           \n", 
4855              "0.666667             12.363205            0.287760             11.743296           \n", 
4856              "0.800000             11.092532            0.280514             11.743296           \n", 
4857              "0.933333             10.566090            0.277619             11.743296           \n", 
4858              "1.066667             9.805807             0.273544             11.743296           \n", 
4859              "1.200000             9.564301             0.272276             11.743296           \n", 
4860              "1.333333             9.015634             0.269442             11.743296           \n", 
4861              "1.466667             8.607765             0.267375             11.743296           \n", 
4862              "1.600000             8.279997             0.265740             11.743296           \n", 
4863              "1.733333             8.474536             0.266708             11.743296           \n", 
4864              "1.866667             8.158973             0.265141             11.743296           \n", 
4865              "2.000000             7.988631             0.264304             11.743296           \n", 
4866              "0.133333             22.224914            0.166231             18.789274           \n", 
4867              "0.266667             21.230874            0.162377             18.789274           \n", 
4868              "0.400000             20.603704            0.160017             18.789274           \n", 
4869              "0.533333             20.327797            0.158996             18.789274           \n", 
4870              "0.666667             18.855377            0.153719             18.789274           \n", 
4871              "0.800000             18.537531            0.152617             18.789274           \n", 
4872              "0.933333             17.508069            0.149138             18.789274           \n", 
4873              "1.066667             16.035604            0.144391             18.789274           \n", 
4874              "1.200000             15.168192            0.141717             18.789274           \n", 
4875              "1.333333             14.431802            0.139516             18.789274           \n", 
4876              "1.466667             14.034137            0.138354             18.789274           \n", 
4877              "1.600000             12.920148            0.135192             18.789274           \n", 
4878              "1.733333             12.653673            0.134456             18.789274           \n", 
4879              "1.866667             12.610864            0.134338             18.789274           \n", 
4880              "2.000000             11.969303            0.132601             18.789274           \n" 
4881          ] 
4882          spin2 = [ 
4883              "title :71@N\n", 
4884              "fields 2 11.7432964915 18.7892743865\n", 
4885              "function CPMG\n", 
4886              "R2 1 10 20\n", 
4887              "Rex 0 100.0 100\n", 
4888              "Tau 0 10.0 100\n", 
4889              "xmgr\n", 
4890              "@ xaxis label \"1/tcp (1/ms)\"\n", 
4891              "@ yaxis label \"R2(tcp) (rad/s)\"\n", 
4892              "@ xaxis ticklabel format decimal\n", 
4893              "@ yaxis ticklabel format decimal\n", 
4894              "@ xaxis ticklabel char size 0.8\n", 
4895              "@ yaxis ticklabel char size 0.8\n", 
4896              "@ world xmin 0.0\n", 
4897              "data\n", 
4898              "0.133333             7.044342             0.170035             11.743296           \n", 
4899              "0.266667             6.781033             0.169228             11.743296           \n", 
4900              "0.400000             6.467623             0.168279             11.743296           \n", 
4901              "0.533333             6.333340             0.167876             11.743296           \n", 
4902              "0.666667             6.323238             0.167846             11.743296           \n", 
4903              "0.800000             6.005245             0.166902             11.743296           \n", 
4904              "0.933333             5.767052             0.166203             11.743296           \n", 
4905              "1.066667             5.476968             0.165361             11.743296           \n", 
4906              "1.200000             5.469949             0.165341             11.743296           \n", 
4907              "1.333333             5.295113             0.164838             11.743296           \n", 
4908              "1.466667             5.435648             0.165242             11.743296           \n", 
4909              "1.600000             5.410400             0.165169             11.743296           \n", 
4910              "1.733333             5.437554             0.165247             11.743296           \n", 
4911              "1.866667             5.176844             0.164501             11.743296           \n", 
4912              "2.000000             5.227232             0.164644             11.743296           \n", 
4913              "0.133333             11.530903            0.081928             18.789274           \n", 
4914              "0.266667             10.983094            0.081041             18.789274           \n", 
4915              "0.400000             10.512403            0.080294             18.789274           \n", 
4916              "0.533333             9.984805             0.079473             18.789274           \n", 
4917              "0.666667             9.573163             0.078845             18.789274           \n", 
4918              "0.800000             9.178810             0.078253             18.789274           \n", 
4919              "0.933333             8.935719             0.077893             18.789274           \n", 
4920              "1.066667             8.610147             0.077416             18.789274           \n", 
4921              "1.200000             8.353778             0.077045             18.789274           \n", 
4922              "1.333333             8.173729             0.076787             18.789274           \n", 
4923              "1.466667             8.091607             0.076670             18.789274           \n", 
4924              "1.600000             7.706420             0.076126             18.789274           \n", 
4925              "1.733333             7.709125             0.076129             18.789274           \n", 
4926              "1.866667             7.610856             0.075992             18.789274           \n", 
4927              "2.000000             7.552584             0.075911             18.789274           \n", 
4928          ] 
4929   
4930          # Check the batch file. 
4931          print("\nChecking the batch file.") 
4932          file = open("%s%sbatch_run.sh" % (ds.tmpdir, sep)) 
4933          lines = file.readlines() 
4934          file.close() 
4935          for i in range(len(lines)): 
4936              self.assertEqual(batch_file[i], lines[i]) 
4937   
4938          # Check spin :70@N. 
4939          print("\nChecking the spin :70@N input file.") 
4940          file = open("%s%sspin%s.in" % (ds.tmpdir, sep, '_70_N')) 
4941          lines = file.readlines() 
4942          file.close() 
4943          for i in range(len(spin1)): 
4944              print("%s\"%s\\n\"," % (" "*12, lines[i][:-1])) 
4945          for i in range(len(lines)): 
4946              self.assertEqual(spin1[i], lines[i]) 
4947   
4948          # Check spin :71@N. 
4949          print("\nChecking the spin :71@N input file.") 
4950          file = open("%s%sspin%s.in" % (ds.tmpdir, sep, '_71_N')) 
4951          lines = file.readlines() 
4952          file.close() 
4953          for i in range(len(lines)): 
4954              print("%s\"%s\\n\"," % (" "*12, lines[i][:-1])) 
4955          for i in range(len(spin2)): 
4956              self.assertEqual(spin2[i], lines[i]) 
4957   
4958   
4959 -    def test_korzhnev_2005_15n_dq_data(self): 
4960          """Optimisation of the Korzhnev et al., 2005 15N DQ CPMG data using the 'NS MMQ 2-site' model. 
4961   
4962          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
4963   
4964          Here only the 15N DQ data will be optimised.  The values found by cpmg_fit using just this data are: 
4965   
4966              - r2 = {'500': 9.487269007171426, '600': 11.718267257562591, '800': 13.624551743116887}, 
4967              - pA = 0.965402506690231, 
4968              - dw = 0.805197170133360, 
4969              - dwH = -0.595536627771890, 
4970              - kex = 569.003663067619868, 
4971              - chi2 = 9.297671357952812. 
4972          """ 
4973   
4974          # Base data setup. 
4975          self.setup_korzhnev_2005_data(data_list=['DQ']) 
4976   
4977          # Alias the spin. 
4978          spin = return_spin(":9@N") 
4979   
4980          # The R20 keys. 
4981          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=500e6) 
4982          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=600e6) 
4983          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=800e6) 
4984   
4985          # Set the initial parameter values. 
4986          spin.r2 = {r20_key1: 9.48527908326952, r20_key2: 11.7135951595536, r20_key3: 13.6153887849344} 
4987          spin.pA = 0.965638501551899 
4988          spin.dw = 2.8537583461577 
4989          spin.dwH = -0.387633062766635 
4990          spin.kex = 573.704033851592 
4991   
4992          # Low precision optimisation. 
4993          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
4994   
4995          # Monte Carlo simulations. 
4996          self.interpreter.monte_carlo.setup(number=2) 
4997          self.interpreter.monte_carlo.create_data(method='back_calc') 
4998          self.interpreter.monte_carlo.initial_values() 
4999          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5000          self.interpreter.monte_carlo.error_analysis() 
5001   
5002          # Plot the dispersion curves. 
5003          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5004   
5005          # Save the results. 
5006          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5007   
5008          # Printout. 
5009          print("\n\nOptimised parameters:\n") 
5010          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5011          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5012          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5013          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5014          print("%-20s %20.15g" % ("pA", spin.pA)) 
5015          print("%-20s %20.15g" % ("dw", spin.dw)) 
5016          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5017          print("%-20s %20.15g" % ("kex", spin.kex)) 
5018          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5019   
5020          # Checks for residue :9. 
5021          self.assertAlmostEqual(spin.r2[r20_key1], 9.4870656457415, 2) 
5022          self.assertAlmostEqual(spin.r2[r20_key2], 11.7183291788929, 2) 
5023          self.assertAlmostEqual(spin.r2[r20_key3], 13.6241729933153, 2) 
5024          self.assertAlmostEqual(spin.pA, 0.965405468217295, 4) 
5025          self.assertAlmostEqual(spin.dw, 2.76835528427355, 1) 
5026          self.assertAlmostEqual(spin.dwH, -0.396489341086363, 2) 
5027          self.assertAlmostEqual(spin.kex/1000, 569.06937047601/1000, 3) 
5028          self.assertAlmostEqual(spin.chi2, 9.29767487125257, 2) 
5029   
5030   
5031 -    def test_korzhnev_2005_15n_mq_data(self): 
5032          """Optimisation of the Korzhnev et al., 2005 15N MQ CPMG data using the 'NS MMQ 2-site' model. 
5033   
5034          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5035   
5036          Here only the 15N MQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5037   
5038              - r2 = {'500': 5.993083514798655, '600': 6.622184438384841, '800': 8.640765919352019}, 
5039              - pA = 0.930027999814003, 
5040              - dw = 4.338620619954370, 
5041              - dwH = -0.274250775560818, 
5042              - kex = 344.613362916544475, 
5043              - chi2 = 10.367733168217050. 
5044          """ 
5045   
5046          # Base data setup. 
5047          self.setup_korzhnev_2005_data(data_list=['MQ']) 
5048   
5049          # Alias the spin. 
5050          spin = return_spin(":9@N") 
5051   
5052          # The R20 keys. 
5053          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=500e6) 
5054          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=600e6) 
5055          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
5056   
5057          # Set the initial parameter values. 
5058          spin.r2 = {r20_key1: 6.02016436619016, r20_key2: 6.65421500772308, r20_key3: 8.6729591487622} 
5059          spin.pA = 0.930083249288083 
5060          spin.dw = 4.33890689462363 
5061          spin.dwH = -0.274316585638047 
5062          spin.kex = 344.329651956132 
5063   
5064          # Low precision optimisation. 
5065          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
5066   
5067          # Monte Carlo simulations. 
5068          self.interpreter.monte_carlo.setup(number=2) 
5069          self.interpreter.monte_carlo.create_data(method='back_calc') 
5070          self.interpreter.monte_carlo.initial_values() 
5071          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5072          self.interpreter.monte_carlo.error_analysis() 
5073   
5074          # Plot the dispersion curves. 
5075          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5076   
5077          # Save the results. 
5078          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5079   
5080          # Printout. 
5081          print("\n\nOptimised parameters:\n") 
5082          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5083          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5084          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5085          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5086          print("%-20s %20.15g" % ("pA", spin.pA)) 
5087          print("%-20s %20.15g" % ("dw", spin.dw)) 
5088          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5089          print("%-20s %20.15g" % ("kex", spin.kex)) 
5090          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5091   
5092          # Checks for residue :9. 
5093          self.assertAlmostEqual(spin.r2[r20_key1], 5.99503641023038, 1) 
5094          self.assertAlmostEqual(spin.r2[r20_key2], 6.62432897608527, 1) 
5095          self.assertAlmostEqual(spin.r2[r20_key3], 8.64278915809492, 1) 
5096          self.assertAlmostEqual(spin.pA, 0.930036474040713, 3) 
5097          self.assertAlmostEqual(spin.dw, 4.33848403058432, 2) 
5098          self.assertAlmostEqual(spin.dwH, -0.274246558825267, 3) 
5099          self.assertAlmostEqual(spin.kex/1000, 344.626563267384/1000, 3) 
5100          self.assertAlmostEqual(spin.chi2, 10.3677362372789, 2) 
5101   
5102   
5103 -    def test_korzhnev_2005_15n_sq_data(self): 
5104          """Optimisation of the Korzhnev et al., 2005 15N SQ CPMG data using the 'NS MMQ 2-site' model. 
5105   
5106          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5107   
5108          Here only the 15N SQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5109   
5110              - r2 = {'500': 8.335037972570017, '600': 8.761366016417508, '800': 10.225001019091822}, 
5111              - pA = 0.950003458294991, 
5112              - dw = 4.358402855315123, 
5113              - kex = 429.906473361926999, 
5114              - chi2 = 17.393331915567252. 
5115          """ 
5116   
5117          # Base data setup. 
5118          self.setup_korzhnev_2005_data(data_list=['SQ']) 
5119   
5120          # Alias the spin. 
5121          spin = return_spin(":9@N") 
5122   
5123          # The R20 keys. 
5124          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
5125          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=600e6) 
5126          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
5127   
5128          # Set the initial parameter values. 
5129          spin.r2 = {r20_key1: 8.334232330326190, r20_key2: 8.756773997879968, r20_key3: 10.219320492033058} 
5130          spin.pA = 0.950310172115387 
5131          spin.dw = 4.356737157889636 
5132          spin.kex = 433.176323890829849 
5133   
5134          # Low precision optimisation. 
5135          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
5136   
5137          # Monte Carlo simulations. 
5138          self.interpreter.monte_carlo.setup(number=2) 
5139          self.interpreter.monte_carlo.create_data(method='back_calc') 
5140          self.interpreter.monte_carlo.initial_values() 
5141          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5142          self.interpreter.monte_carlo.error_analysis() 
5143   
5144          # Plot the dispersion curves. 
5145          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5146   
5147          # Save the results. 
5148          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5149   
5150          # Printout. 
5151          print("\n\nOptimised parameters:\n") 
5152          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5153          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5154          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5155          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5156          print("%-20s %20.15g" % ("pA", spin.pA)) 
5157          print("%-20s %20.15g" % ("dw", spin.dw)) 
5158          print("%-20s %20.15g" % ("kex", spin.kex)) 
5159          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5160   
5161          # Checks for residue :9. 
5162          self.assertAlmostEqual(spin.r2[r20_key1], 8.33499994313902, 2) 
5163          self.assertAlmostEqual(spin.r2[r20_key2], 8.76118738798082, 2) 
5164          self.assertAlmostEqual(spin.r2[r20_key3], 10.2250821829928, 1) 
5165          self.assertAlmostEqual(spin.pA, 0.950000281516303, 3) 
5166          self.assertAlmostEqual(spin.dw, 4.35845318983581, 2) 
5167          self.assertAlmostEqual(spin.kex/1000, 429.874510184149/1000, 2) 
5168          self.assertAlmostEqual(spin.chi2, 17.3933357984425, 1) 
5169   
5170   
5171 -    def test_korzhnev_2005_15n_zq_data(self): 
5172          """Optimisation of the Korzhnev et al., 2005 15N ZQ CPMG data using the 'NS MMQ 2-site' model. 
5173   
5174          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5175   
5176          Here only the 15N ZQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5177   
5178              - r2 = {'500': 5.909812628572937, '600': 6.663690132557320, '800': 6.787171647689906}, 
5179              - pA = 0.942452612380140, 
5180              - dw = 0.858972784230892, 
5181              - dwH = 0.087155962730608, 
5182              - kex = 373.219151384798920, 
5183              - chi2 = 23.863208106025152. 
5184          """ 
5185   
5186          # Base data setup. 
5187          self.setup_korzhnev_2005_data(data_list=['ZQ']) 
5188   
5189          # Alias the spin. 
5190          spin = return_spin(":9@N") 
5191   
5192          # The R20 keys. 
5193          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=500e6) 
5194          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=600e6) 
5195          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=800e6) 
5196   
5197          # Set the initial parameter values. 
5198          spin.r2 = {r20_key1: 5.91033272691614, r20_key2: 6.66368695342258, r20_key3: 6.78922219135537} 
5199          spin.pA = 0.942457332074014 
5200          spin.dw = 0.850592422908884 
5201          spin.dwH = 0.0881272284455416 
5202          spin.kex = 372.745483351305 
5203   
5204          # Low precision optimisation. 
5205          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
5206   
5207          # Monte Carlo simulations. 
5208          self.interpreter.monte_carlo.setup(number=2) 
5209          self.interpreter.monte_carlo.create_data(method='back_calc') 
5210          self.interpreter.monte_carlo.initial_values() 
5211          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5212          self.interpreter.monte_carlo.error_analysis() 
5213   
5214          # Plot the dispersion curves. 
5215          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5216   
5217          # Save the results. 
5218          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5219   
5220          # Printout. 
5221          print("\n\nOptimised parameters:\n") 
5222          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5223          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5224          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5225          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5226          print("%-20s %20.15g" % ("pA", spin.pA)) 
5227          print("%-20s %20.15g" % ("dw", spin.dw)) 
5228          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5229          print("%-20s %20.15g" % ("kex", spin.kex)) 
5230          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5231   
5232          # Checks for residue :9. 
5233          self.assertAlmostEqual(spin.r2[r20_key1], 5.9098385837035, 2) 
5234          self.assertAlmostEqual(spin.r2[r20_key2], 6.66377885876553, 2) 
5235          self.assertAlmostEqual(spin.r2[r20_key3], 6.78717432941353, 2) 
5236          self.assertAlmostEqual(spin.pA, 0.942457141344462, 4) 
5237          self.assertAlmostEqual(spin.dw, 0.84442055695814, 1) 
5238          self.assertAlmostEqual(spin.dwH, 0.0886367674566058, 2) 
5239          self.assertAlmostEqual(spin.kex/1000, 373.243053643367/1000, 3) 
5240          self.assertAlmostEqual(spin.chi2, 23.863211604121, 1) 
5241   
5242   
5243 -    def test_korzhnev_2005_1h_mq_data(self): 
5244          """Optimisation of the Korzhnev et al., 2005 1H MQ CPMG data using the 'NS MMQ 2-site' model. 
5245   
5246          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5247   
5248          Here only the 1H MQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5249   
5250              - r2 = {'500': -0.000016676911302, '600': 0.036594127620440, '800': 2.131014839635728}, 
5251              - pA = 0.936911090448340, 
5252              - dw = 4.325314846914845, 
5253              - dwH = -0.213870168665628, 
5254              - kex = 487.361914835074117, 
5255              - chi2 = 14.870371897291138. 
5256          """ 
5257   
5258          # Base data setup. 
5259          self.setup_korzhnev_2005_data(data_list=['1H MQ']) 
5260   
5261          # Alias the spin. 
5262          spin = return_spin(":9@N") 
5263   
5264          # The R20 keys. 
5265          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=500e6) 
5266          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=600e6) 
5267          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=800e6) 
5268   
5269          # Set the initial parameter values. 
5270          spin.r2 = {r20_key1: 0.000022585022901, r20_key2: 0.039223196112941, r20_key3: 2.136576686700357} 
5271          spin.pA = 0.936884348941701 
5272          spin.dw = 4.326454531583964 
5273          spin.dwH = -0.214026093221782 
5274          spin.kex = 487.043592705469223 
5275   
5276          # Low precision optimisation. 
5277          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=100) 
5278   
5279          # Monte Carlo simulations. 
5280          self.interpreter.monte_carlo.setup(number=2) 
5281          self.interpreter.monte_carlo.create_data(method='back_calc') 
5282          self.interpreter.monte_carlo.initial_values() 
5283          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5284          self.interpreter.monte_carlo.error_analysis() 
5285   
5286          # Plot the dispersion curves. 
5287          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5288   
5289          # Save the results. 
5290          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5291   
5292          # Printout. 
5293          print("\n\nOptimised parameters:\n") 
5294          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5295          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5296          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5297          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5298          print("%-20s %20.15g" % ("pA", spin.pA)) 
5299          print("%-20s %20.15g" % ("dw", spin.dw)) 
5300          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5301          print("%-20s %20.15g" % ("kex", spin.kex)) 
5302          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5303   
5304          # Checks for residue :9. 
5305          self.assertAlmostEqual(spin.r2[r20_key1], 2.48493199969936e-05, 4) 
5306          self.assertAlmostEqual(spin.r2[r20_key2], 0.0382382195911849, 2) 
5307          self.assertAlmostEqual(spin.r2[r20_key3], 2.13397221524655, 2) 
5308          self.assertAlmostEqual(spin.pA, 0.936879359956996, 4) 
5309          self.assertAlmostEqual(spin.dw, 4.32573362253701, 2) 
5310          self.assertAlmostEqual(spin.dwH, -0.213951762275293, 2) 
5311          self.assertAlmostEqual(spin.kex/1000, 487.021196851596/1000, 4) 
5312          self.assertAlmostEqual(spin.chi2, 14.8704048958378, 2) 
5313   
5314   
5315 -    def test_korzhnev_2005_1h_sq_data(self): 
5316          """Optimisation of the Korzhnev et al., 2005 1H SQ CPMG data using the 'NS MMQ 2-site' model. 
5317   
5318          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5319   
5320          Here only the 1H SQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5321   
5322              - r2 = {'500': 6.691697587650816, '600': 6.998915158708793, '800': 5.519267837559072}, 
5323              - pA = 0.946949480545876, 
5324              - dwH = -0.265279672133308, 
5325              - kex = 406.548178869750700, 
5326              - chi2 = 50.400680290545026. 
5327          """ 
5328   
5329          # Base data setup. 
5330          self.setup_korzhnev_2005_data(data_list=['1H SQ']) 
5331   
5332          # Alias the spin. 
5333          spin = return_spin(":9@N") 
5334   
5335          # The R20 keys. 
5336          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=500e6) 
5337          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=600e6) 
5338          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=800e6) 
5339   
5340          # Set the initial parameter values. 
5341          spin.r2 = {r20_key1: 6.69107911078939, r20_key2: 6.99888898689085, r20_key3: 5.52012880268077} 
5342          spin.pA = 0.946990967372467 
5343          spin.dwH = -0.265308128403529 
5344          spin.kex = 406.843250675648 
5345   
5346          # Low precision optimisation. 
5347          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
5348   
5349          # Monte Carlo simulations. 
5350          self.interpreter.monte_carlo.setup(number=2) 
5351          self.interpreter.monte_carlo.create_data(method='back_calc') 
5352          self.interpreter.monte_carlo.initial_values() 
5353          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5354          self.interpreter.monte_carlo.error_analysis() 
5355   
5356          # Plot the dispersion curves. 
5357          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5358   
5359          # Save the results. 
5360          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5361   
5362          # Printout. 
5363          print("\n\nOptimised parameters:\n") 
5364          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5365          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5366          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5367          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5368          print("%-20s %20.15g" % ("pA", spin.pA)) 
5369          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5370          print("%-20s %20.15g" % ("kex", spin.kex)) 
5371          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5372   
5373          # Checks for residue :9. 
5374          self.assertAlmostEqual(spin.r2[r20_key1], 6.69168251154302, 2) 
5375          self.assertAlmostEqual(spin.r2[r20_key2], 6.99900388754043, 2) 
5376          self.assertAlmostEqual(spin.r2[r20_key3], 5.51921590064843, 2) 
5377          self.assertAlmostEqual(spin.pA, 0.946951877648819, 4) 
5378          self.assertAlmostEqual(spin.dwH, -0.265280175525516, 3) 
5379          self.assertAlmostEqual(spin.kex/1000, 406.566453278183/1000, 2) 
5380          self.assertAlmostEqual(spin.chi2, 50.4006836222044, 1) 
5381   
5382   
5383 -    def test_korzhnev_2005_all_data(self): 
5384          """Optimisation of all the Korzhnev et al., 2005 CPMG data using the 'NS MMQ 2-site' model. 
5385   
5386          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5387   
5388          Here all data will be optimised.  The values found by cpmg_fit using just this data are: 
5389   
5390              - r2 = {'H-S 500':  6.671649051677150, 'H-S 600':  6.988634195648529, 'H-S 800':  5.527971316790596, 
5391                      'N-S 500':  8.394988400015988, 'N-S 600':  8.891359568401835, 'N-S 800': 10.405356669006709, 
5392                      'NHZ 500':  5.936446687394352, 'NHZ 600':  6.717058062814535, 'NHZ 800':  6.838733853403030, 
5393                      'NHD 500':  8.593136215779710, 'NHD 600': 10.651511259239674, 'NHD 800': 12.567902357560627, 
5394                      'HNM 500':  7.851325614877817, 'HNM 600':  8.408803624020202, 'HNM 800': 11.227489645758979, 
5395                      'NHM 500':  9.189159145380575, 'NHM 600':  9.856814478405868, 'NHM 800': 11.967910041807118}, 
5396              - pA = 0.943125351763911, 
5397              - dw = 4.421827493809807, 
5398              - dwH = -0.272637034755752, 
5399              - kex = 360.609744568697238, 
5400              - chi2 = 162.589570340050813. 
5401          """ 
5402   
5403          # Base data setup. 
5404          self.setup_korzhnev_2005_data(data_list=['SQ', '1H SQ', 'DQ', 'ZQ', 'MQ', '1H MQ']) 
5405   
5406          # Alias the spin. 
5407          spin = return_spin(":9@N") 
5408   
5409          # The R20 keys. 
5410          r20_key1  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=500e6) 
5411          r20_key2  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=600e6) 
5412          r20_key3  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=800e6) 
5413          r20_key4  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
5414          r20_key5  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=600e6) 
5415          r20_key6  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
5416          r20_key7  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=500e6) 
5417          r20_key8  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=600e6) 
5418          r20_key9  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=800e6) 
5419          r20_key10 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=500e6) 
5420          r20_key11 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=600e6) 
5421          r20_key12 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=800e6) 
5422          r20_key13 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=500e6) 
5423          r20_key14 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=600e6) 
5424          r20_key15 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=800e6) 
5425          r20_key16 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=500e6) 
5426          r20_key17 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=600e6) 
5427          r20_key18 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
5428   
5429          # Set the initial parameter values. 
5430          spin.r2 = { 
5431              r20_key1:   6.67288025927458, r20_key2:   6.98951408255098, r20_key3:   5.52959273852704, 
5432              r20_key4:   8.39471048876782, r20_key5:   8.89290699178799, r20_key6:  10.40770687236930, 
5433              r20_key7:   5.93611174376373, r20_key8:   6.71735669582514, r20_key9:   6.83835225518265, 
5434              r20_key10:  8.59615074668922, r20_key11: 10.65121378892910, r20_key12: 12.57108229191090, 
5435              r20_key13:  7.85956711501608, r20_key14:  8.41891642907918, r20_key15: 11.23620892230380, 
5436              r20_key16:  9.19654863789350, r20_key17:  9.86031627358462, r20_key18: 11.97523755925750 
5437          } 
5438          spin.pA = 0.943129019477673 
5439          spin.dw = 4.42209952545181 
5440          spin.dwH = -0.27258970590969 
5441          spin.kex = 360.516132791038 
5442   
5443          # Low precision optimisation. 
5444          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=10) 
5445   
5446          # Monte Carlo simulations. 
5447          self.interpreter.monte_carlo.setup(number=2) 
5448          self.interpreter.monte_carlo.create_data(method='back_calc') 
5449          self.interpreter.monte_carlo.initial_values() 
5450          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5451          self.interpreter.monte_carlo.error_analysis() 
5452   
5453          # Plot the dispersion curves. 
5454          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5455   
5456          # Save the results. 
5457          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5458   
5459          # Printout. 
5460          print("\n\nOptimised parameters:\n") 
5461          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5462          print("%-20s %20.15g" % ("R2 (1H SQ - 500 MHz)", spin.r2[r20_key1])) 
5463          print("%-20s %20.15g" % ("R2 (1H SQ - 600 MHz)", spin.r2[r20_key2])) 
5464          print("%-20s %20.15g" % ("R2 (1H SQ - 800 MHz)", spin.r2[r20_key3])) 
5465          print("%-20s %20.15g" % ("R2 (SQ - 500 MHz)", spin.r2[r20_key4])) 
5466          print("%-20s %20.15g" % ("R2 (SQ - 600 MHz)", spin.r2[r20_key5])) 
5467          print("%-20s %20.15g" % ("R2 (SQ - 800 MHz)", spin.r2[r20_key6])) 
5468          print("%-20s %20.15g" % ("R2 (ZQ - 500 MHz)", spin.r2[r20_key7])) 
5469          print("%-20s %20.15g" % ("R2 (ZQ - 600 MHz)", spin.r2[r20_key8])) 
5470          print("%-20s %20.15g" % ("R2 (ZQ - 800 MHz)", spin.r2[r20_key9])) 
5471          print("%-20s %20.15g" % ("R2 (DQ - 500 MHz)", spin.r2[r20_key10])) 
5472          print("%-20s %20.15g" % ("R2 (DQ - 600 MHz)", spin.r2[r20_key11])) 
5473          print("%-20s %20.15g" % ("R2 (DQ - 800 MHz)", spin.r2[r20_key12])) 
5474          print("%-20s %20.15g" % ("R2 (1H MQ - 500 MHz)", spin.r2[r20_key13])) 
5475          print("%-20s %20.15g" % ("R2 (1H MQ - 600 MHz)", spin.r2[r20_key14])) 
5476          print("%-20s %20.15g" % ("R2 (1H MQ - 800 MHz)", spin.r2[r20_key15])) 
5477          print("%-20s %20.15g" % ("R2 (MQ - 500 MHz)", spin.r2[r20_key16])) 
5478          print("%-20s %20.15g" % ("R2 (MQ - 600 MHz)", spin.r2[r20_key17])) 
5479          print("%-20s %20.15g" % ("R2 (MQ - 800 MHz)", spin.r2[r20_key18])) 
5480          print("%-20s %20.15g" % ("pA", spin.pA)) 
5481          print("%-20s %20.15g" % ("dw", spin.dw)) 
5482          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5483          print("%-20s %20.15g" % ("kex", spin.kex)) 
5484          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5485   
5486          # Checks for residue :9. 
5487          self.assertAlmostEqual(spin.r2[r20_key1],  6.67288025927458, 4) 
5488          self.assertAlmostEqual(spin.r2[r20_key2],  6.98951408255098, 4) 
5489          self.assertAlmostEqual(spin.r2[r20_key3],  5.52959273852704, 4) 
5490          self.assertAlmostEqual(spin.r2[r20_key4],  8.39471048876782, 4) 
5491          self.assertAlmostEqual(spin.r2[r20_key5],  8.89290699178799, 4) 
5492          self.assertAlmostEqual(spin.r2[r20_key6],  10.4077068723693, 4) 
5493          self.assertAlmostEqual(spin.r2[r20_key7],  5.93611174376373, 4) 
5494          self.assertAlmostEqual(spin.r2[r20_key8],  6.71735669582514, 4) 
5495          self.assertAlmostEqual(spin.r2[r20_key9],  6.83835225518265, 4) 
5496          self.assertAlmostEqual(spin.r2[r20_key10], 8.59615074668922, 4) 
5497          self.assertAlmostEqual(spin.r2[r20_key11], 10.6512137889291, 4) 
5498          self.assertAlmostEqual(spin.r2[r20_key12], 12.5710822919109, 4) 
5499          self.assertAlmostEqual(spin.r2[r20_key13], 7.85956711501608, 4) 
5500          self.assertAlmostEqual(spin.r2[r20_key14], 8.41891642907918, 4) 
5501          self.assertAlmostEqual(spin.r2[r20_key15], 11.2362089223038, 4) 
5502          self.assertAlmostEqual(spin.r2[r20_key16], 9.1965486378935, 4) 
5503          self.assertAlmostEqual(spin.r2[r20_key17], 9.86031627358462, 4) 
5504          self.assertAlmostEqual(spin.r2[r20_key18], 11.9752375592575, 4) 
5505          self.assertAlmostEqual(spin.pA, 0.943129019477673, 4) 
5506          self.assertAlmostEqual(spin.dw, 4.42209952545181, 4) 
5507          self.assertAlmostEqual(spin.dwH, -0.27258970590969, 4) 
5508          self.assertAlmostEqual(spin.kex/1000, 360.516132791038/1000, 4) 
5509          self.assertAlmostEqual(spin.chi2/1000, 162.596331278669/1000, 3) 
5510   
5511   
5512 -    def test_korzhnev_2005_all_data_disp_speed_bug(self): 
5513          """Optimisation of all the Korzhnev et al., 2005 CPMG data using the 'NS MMQ 2-site' model. 
5514   
5515          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5516   
5517          Here all data will be optimised.  The values found by cpmg_fit using just this data are: 
5518   
5519              - r2 = {'H-S 500':  6.671649051677150, 'H-S 600':  6.988634195648529, 'H-S 800':  5.527971316790596, 
5520                      'N-S 500':  8.394988400015988, 'N-S 600':  8.891359568401835, 'N-S 800': 10.405356669006709, 
5521                      'NHZ 500':  5.936446687394352, 'NHZ 600':  6.717058062814535, 'NHZ 800':  6.838733853403030, 
5522                      'NHD 500':  8.593136215779710, 'NHD 600': 10.651511259239674, 'NHD 800': 12.567902357560627, 
5523                      'HNM 500':  7.851325614877817, 'HNM 600':  8.408803624020202, 'HNM 800': 11.227489645758979, 
5524                      'NHM 500':  9.189159145380575, 'NHM 600':  9.856814478405868, 'NHM 800': 11.967910041807118}, 
5525              - pA = 0.943125351763911, 
5526              - dw = 4.421827493809807, 
5527              - dwH = -0.272637034755752, 
5528              - kex = 360.609744568697238, 
5529              - chi2 = 162.589570340050813. 
5530          """ 
5531   
5532          # Base data setup. 
5533          self.setup_korzhnev_2005_data(data_list=['SQ', '1H SQ', 'DQ', 'ZQ', 'MQ', '1H MQ']) 
5534   
5535          # Alias the spin. 
5536          spin = return_spin(":9@N") 
5537   
5538          # The R20 keys. 
5539          r20_key1  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=500e6) 
5540          r20_key2  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=600e6) 
5541          r20_key3  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=800e6) 
5542          r20_key4  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
5543          r20_key5  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=600e6) 
5544          r20_key6  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
5545          r20_key7  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=500e6) 
5546          r20_key8  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=600e6) 
5547          r20_key9  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=800e6) 
5548          r20_key10 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=500e6) 
5549          r20_key11 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=600e6) 
5550          r20_key12 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=800e6) 
5551          r20_key13 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=500e6) 
5552          r20_key14 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=600e6) 
5553          r20_key15 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=800e6) 
5554          r20_key16 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=500e6) 
5555          r20_key17 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=600e6) 
5556          r20_key18 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
5557   
5558          # Set the initial parameter values. 
5559          spin.r2 = { 
5560              r20_key1:   6.67288025927458, r20_key2:   6.98951408255098, r20_key3:   5.52959273852704, 
5561              r20_key4:   8.39471048876782, r20_key5:   8.89290699178799, r20_key6:  10.40770687236930, 
5562              r20_key7:   5.93611174376373, r20_key8:   6.71735669582514, r20_key9:   6.83835225518265, 
5563              r20_key10:  8.59615074668922, r20_key11: 10.65121378892910, r20_key12: 12.57108229191090, 
5564              r20_key13:  7.85956711501608, r20_key14:  8.41891642907918, r20_key15: 11.23620892230380, 
5565              r20_key16:  9.19654863789350, r20_key17:  9.86031627358462, r20_key18: 11.97523755925750 
5566          } 
5567          spin.pA = 0.943129019477673 
5568          spin.dw = 4.42209952545181 
5569          spin.dwH = -0.27258970590969 
5570          spin.kex = 360.516132791038 
5571   
5572          # Calc the chi2 values at these parameters. 
5573          self.interpreter.minimise.calculate(verbosity=1) 
5574   
5575          # Printout. 
5576          print("\n\nOptimised parameters:\n") 
5577          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5578          print("%-20s %20.15g" % ("R2 (1H SQ - 500 MHz)", spin.r2[r20_key1])) 
5579          print("%-20s %20.15g" % ("R2 (1H SQ - 600 MHz)", spin.r2[r20_key2])) 
5580          print("%-20s %20.15g" % ("R2 (1H SQ - 800 MHz)", spin.r2[r20_key3])) 
5581          print("%-20s %20.15g" % ("R2 (SQ - 500 MHz)", spin.r2[r20_key4])) 
5582          print("%-20s %20.15g" % ("R2 (SQ - 600 MHz)", spin.r2[r20_key5])) 
5583          print("%-20s %20.15g" % ("R2 (SQ - 800 MHz)", spin.r2[r20_key6])) 
5584          print("%-20s %20.15g" % ("R2 (ZQ - 500 MHz)", spin.r2[r20_key7])) 
5585          print("%-20s %20.15g" % ("R2 (ZQ - 600 MHz)", spin.r2[r20_key8])) 
5586          print("%-20s %20.15g" % ("R2 (ZQ - 800 MHz)", spin.r2[r20_key9])) 
5587          print("%-20s %20.15g" % ("R2 (DQ - 500 MHz)", spin.r2[r20_key10])) 
5588          print("%-20s %20.15g" % ("R2 (DQ - 600 MHz)", spin.r2[r20_key11])) 
5589          print("%-20s %20.15g" % ("R2 (DQ - 800 MHz)", spin.r2[r20_key12])) 
5590          print("%-20s %20.15g" % ("R2 (1H MQ - 500 MHz)", spin.r2[r20_key13])) 
5591          print("%-20s %20.15g" % ("R2 (1H MQ - 600 MHz)", spin.r2[r20_key14])) 
5592          print("%-20s %20.15g" % ("R2 (1H MQ - 800 MHz)", spin.r2[r20_key15])) 
5593          print("%-20s %20.15g" % ("R2 (MQ - 500 MHz)", spin.r2[r20_key16])) 
5594          print("%-20s %20.15g" % ("R2 (MQ - 600 MHz)", spin.r2[r20_key17])) 
5595          print("%-20s %20.15g" % ("R2 (MQ - 800 MHz)", spin.r2[r20_key18])) 
5596          print("%-20s %20.15g" % ("pA", spin.pA)) 
5597          print("%-20s %20.15g" % ("dw", spin.dw)) 
5598          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5599          print("%-20s %20.15g" % ("kex", spin.kex)) 
5600          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5601   
5602          # Checks for residue :9. 
5603          self.assertAlmostEqual(spin.chi2/1000, 162.511988511609/1000, 3) 
5604   
5605   
5606 -    def test_kteilum_fmpoulsen_makke_check_graphs(self): 
5607          """Check of all possible dispersion graphs from optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5608   
5609          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
5610   
5611          Figure 3 shows the ln( k_a [s^-1]) for different concentrations of GuHCl. The precise values are: 
5612   
5613            - [GuHCL][M] ln(k_a[s^-1]) k_a[s^-1] 
5614            - 0.483 0.89623903 2.4503699912708878 
5615            - 0.545 1.1694838 
5616            - 0.545 1.1761503 
5617            - 0.622 1.294 
5618            - 0.669 1.5176493 
5619            - 0.722 1.6238791 
5620            - 0.813 1.9395758 
5621            - 1.011 2.3558415 10.547000429321157 
5622          """ 
5623   
5624          # Base data setup. 
5625          model = 'TSMFK01' 
5626          expfolder = "acbp_cpmg_disp_048MGuHCl_40C_041223" 
5627          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model=model, expfolder=expfolder) 
5628   
5629          # Alias the spins. 
5630          res61L = cdp.mol[0].res[0].spin[0] 
5631   
5632          # The R20 keys. 
5633          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086220e6) 
5634   
5635          # Set the initial parameter values. 
5636          res61L.r2a = {r20_key1: 8.0} 
5637          res61L.dw = 6.5 
5638          res61L.k_AB = 2.5 
5639   
5640          # Low precision optimisation. 
5641          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5642   
5643          # Start testing all possible combinations of graphs. 
5644          y_axis_types = [Y_AXIS_R2_EFF, Y_AXIS_R2_R1RHO] 
5645          x_axis_types = [X_AXIS_DISP, X_AXIS_THETA, X_AXIS_W_EFF] 
5646          interpolate_types = [INTERPOLATE_DISP] 
5647   
5648          # Write to temp folder. 
5649          result_dir_name = ds.tmpdir 
5650          result_folders = [model] 
5651          spin_id = ":61@N" 
5652   
5653          # Loop through all possible combinations of y_axis, x_axis and interpolation. 
5654          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'KTeilum_FMPoulsen_MAkke_2006'+sep+expfolder+sep+'check_graphs' 
5655   
5656          for result_folder in result_folders: 
5657              for y_axis in y_axis_types: 
5658                  for x_axis in x_axis_types: 
5659                      for interpolate in interpolate_types: 
5660                          # Determine file name: 
5661                          file_name_ini = return_grace_file_name_ini(y_axis=y_axis, x_axis=x_axis, interpolate=interpolate) 
5662   
5663                          # Make the file name. 
5664                          file_name = "%s%s.agr" % (file_name_ini, spin_id.replace('#', '_').replace(':', '_').replace('@', '_')) 
5665   
5666                          # Write the curves. 
5667                          dir = result_dir_name+sep+result_folder 
5668                          print("Plotting combination of %s, %s, %s"%(y_axis, x_axis, interpolate)) 
5669                          self.interpreter.relax_disp.plot_disp_curves(dir=dir, y_axis=y_axis, x_axis=x_axis, interpolate=interpolate, force=True) 
5670   
5671                          # Get the file path. 
5672                          file_path = get_file_path(file_name, dir) 
5673   
5674                          # Test the plot file exists. 
5675                          print("Testing file access to graph: %s"%file_path) 
5676                          self.assert_(access(file_path, F_OK)) 
5677   
5678                          # Now open, and compare content, line by line. 
5679                          file_prod = open(file_path) 
5680                          lines_prod = file_prod.readlines() 
5681                          file_prod.close() 
5682   
5683                          # Define file to compare against. 
5684                          dir_comp = data_path+sep+result_folder 
5685                          file_path_comp = get_file_path(file_name, dir_comp) 
5686                          file_comp = open(file_path_comp) 
5687                          lines_comp = file_comp.readlines() 
5688                          file_comp.close() 
5689   
5690                          ## Assert number of lines is equal. 
5691                          self.assertEqual(len(lines_prod), len(lines_comp)) 
5692                          for j in range(len(lines_prod)): 
5693                              # Make the string test 
5694                              first_char = lines_prod[j][0] 
5695                              if first_char in ["@", "&"]: 
5696                                  self.assertEqual(lines_prod[j], lines_comp[j]) 
5697                              else: 
5698                                  # Split string in x, y, error. 
5699                                  # The error would change per run. 
5700                                  x_prod, y_prod, y_prod_err = lines_prod[j].split() 
5701                                  x_comp, y_comp, y_comp_err = lines_comp[j].split() 
5702                                  self.assertAlmostEqual(float(x_prod), float(x_comp)) 
5703                                  self.assertAlmostEqual(float(y_prod), float(y_comp)) 
5704                                  self.assertAlmostEqual(float(y_prod_err), float(y_comp_err)) 
5705   
5706   
5707 -    def test_kteilum_fmpoulsen_makke_cpmg_data_048m_guhcl_to_cr72(self): 
5708          """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5709   
5710          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
5711          """ 
5712   
5713          # Base data setup. 
5714          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='CR72', expfolder="acbp_cpmg_disp_048MGuHCl_40C_041223") 
5715   
5716          # Alias the spins. 
5717          res61L = cdp.mol[0].res[0].spin[0] 
5718   
5719          # The R20 keys. 
5720          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086220e6) 
5721   
5722          # Set the initial parameter values. 
5723          res61L.r2 = {r20_key1: 8.0} 
5724          res61L.pA = 0.9 
5725          res61L.dw = 6.0 
5726          res61L.kex = 600.0 
5727   
5728          # Low precision optimisation. 
5729          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5730   
5731          # Printout. 
5732          print("\n\nOptimised parameters:\n") 
5733          print("%-20s %-20s" % ("Parameter", "Value (:61)")) 
5734          print("%-20s %20.15g" % ("R2 (600 MHz)", res61L.r2[r20_key1])) 
5735          print("%-20s %20.15g" % ("pA", res61L.pA)) 
5736          print("%-20s %20.15g" % ("dw", res61L.dw)) 
5737          print("%-20s %20.15g" % ("kex", res61L.kex)) 
5738          print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 
5739   
5740          # Checks for residue :61. Calculated for 500 Monte Carlo simulations. 
5741          self.assertAlmostEqual(res61L.r2[r20_key1], 8.69277980194016, 4) 
5742          self.assertAlmostEqual(res61L.pA, 0.9943781590842946, 5) 
5743          self.assertAlmostEqual(res61L.dw, 6.389453131263374, 3) 
5744          self.assertAlmostEqual(res61L.kex, 609.262167216419, 0) 
5745          self.assertAlmostEqual(res61L.chi2, 65.99987828889657, 5) 
5746   
5747          # Test the conversion to k_AB from kex and pA. 
5748          self.assertEqual(res61L.k_AB, res61L.kex * (1.0 - res61L.pA)) 
5749   
5750          # Test the conversion to k_BA from kex and pA. 
5751          self.assertEqual(res61L.k_BA, res61L.kex * res61L.pA) 
5752   
5753   
5754 -    def test_kteilum_fmpoulsen_makke_cpmg_data_048m_guhcl_to_cr72_full(self): 
5755          """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5756   
5757          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
5758          """ 
5759   
5760          # Base data setup. 
5761          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='CR72 full', expfolder="acbp_cpmg_disp_048MGuHCl_40C_041223") 
5762   
5763          # Alias the spins. 
5764          res61L = cdp.mol[0].res[0].spin[0] 
5765   
5766          # The R20 keys. 
5767          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086220e6) 
5768   
5769          # Set the initial parameter values. 
5770          res61L.r2a = {r20_key1: 8.0} 
5771          res61L.r2b = {r20_key1: 105.0} 
5772          res61L.pA = 0.9 
5773          res61L.dw = 6.0 
5774          res61L.kex = 500.0 
5775   
5776          # Low precision optimisation. 
5777          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5778   
5779          # Printout. 
5780          print("\n\nOptimised parameters:\n") 
5781          print("%-20s %-20s" % ("Parameter", "Value (:61)")) 
5782          print("%-20s %20.15g" % ("R2A (600 MHz)", res61L.r2a[r20_key1])) 
5783          print("%-20s %20.15g" % ("R2B (600 MHz)", res61L.r2b[r20_key1])) 
5784          print("%-20s %20.15g" % ("pA", res61L.pA)) 
5785          print("%-20s %20.15g" % ("dw", res61L.dw)) 
5786          print("%-20s %20.15g" % ("kex", res61L.kex)) 
5787          print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 
5788   
5789          # Checks for residue :61. Calculated for 500 Monte Carlo simulations. 
5790          self.assertAlmostEqual(res61L.r2a[r20_key1], 8.044428899438309, 0) 
5791          self.assertAlmostEqual(res61L.r2b[r20_key1], 105.11894506392449, -2) 
5792          self.assertAlmostEqual(res61L.pA, 0.992066883657578, 2) 
5793          self.assertAlmostEqual(res61L.dw, 6.389453586338883, 3) 
5794          self.assertAlmostEqual(res61L.kex, 513.483608742063, -2) 
5795          self.assertAlmostEqual(res61L.chi2, 65.99987828890289, 5) 
5796   
5797   
5798 -    def test_kteilum_fmpoulsen_makke_cpmg_data_048m_guhcl_to_tsmfk01(self): 
5799          """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5800   
5801          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
5802   
5803          Figure 3 shows the ln( k_a [s^-1]) for different concentrations of GuHCl. The precise values are: 
5804   
5805            - [GuHCL][M] ln(k_a[s^-1]) k_a[s^-1] 
5806            - 0.483 0.89623903 2.4503699912708878 
5807            - 0.545 1.1694838 
5808            - 0.545 1.1761503 
5809            - 0.622 1.294 
5810            - 0.669 1.5176493 
5811            - 0.722 1.6238791 
5812            - 0.813 1.9395758 
5813            - 1.011 2.3558415 10.547000429321157 
5814          """ 
5815   
5816          # Base data setup. 
5817          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='TSMFK01', expfolder="acbp_cpmg_disp_048MGuHCl_40C_041223") 
5818   
5819          # Alias the spins. 
5820          res61L = cdp.mol[0].res[0].spin[0] 
5821   
5822          # The R20 keys. 
5823          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086220e6) 
5824   
5825          # Set the initial parameter values. 
5826          res61L.r2a = {r20_key1: 8.0} 
5827          res61L.dw = 6.5 
5828          res61L.k_AB = 2.5 
5829   
5830          # Low precision optimisation. 
5831          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5832   
5833          # Printout. 
5834          print("\n\nOptimised parameters:\n") 
5835          print("%-20s %-20s" % ("Parameter", "Value (:61)")) 
5836          print("%-20s %20.15g" % ("R2A (600 MHz)", res61L.r2a[r20_key1])) 
5837          print("%-20s %20.15g" % ("dw", res61L.dw)) 
5838          print("%-20s %20.15g" % ("k_AB", res61L.k_AB)) 
5839          print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 
5840   
5841          # Checks for residue :61. Reference values from paper 
5842   
5843          self.assertAlmostEqual(res61L.k_AB, 2.45, 1) 
5844   
5845   
5846 -    def test_kteilum_fmpoulsen_makke_cpmg_data_101m_guhcl_to_tsmfk01(self): 
5847          """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5848   
5849          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 1.01 M GuHCl (guanidine hydrochloride). 
5850   
5851          The comparison is to Figure 2, which is for dataset with 1 M GuHCl.  The reported results are expected to be in rad.s^-1.  Conversion into relax stored values is preferably. 
5852   
5853          Representative 15N CPMG relaxation dispersion curve measured on the cross peaks from residue L61 in folded ACBP at pH 5.3, 1 M GuHCl, and 40C: 
5854   
5855            1. The dotted line represents a residue-specific fit of all parameters in Eq. 1: 
5856              - k_AB = 11.3 +/- 0.7 s^-1, 
5857              - dw = (2.45 +/- 0.09) * 10^3 s^-1, 
5858              - R2 = 8.0 +/- 0.5 s^-1. 
5859   
5860            2. The solid line represents a global fit of k_AB to all protein residues and a residue-specific fit of dw and R2.: 
5861              - k_AB = 10.55 +/- 0.08 s^-1, 
5862              - dw = (2.44 +/- 0.08) * 10^3 s^-1, 
5863              - R2 = 8.4 +/- 0.3 s^-1. 
5864   
5865          Conversion of paper results to relax results is performed by: 
5866   
5867            - dw(ppm) = dw(rad.s^-1) * 10^6 * 1/(2*pi) * (gyro1H/(gyro15N*spectrometer_freq)) = 2.45E3 * 1E6 / (2 * math.pi) * (26.7522212E7/(-2.7126E7 * 599.8908622E6)) = -6.41 ppm. 
5868   
5869          Figure 3 shows the ln( k_a [s^-1]) for different concentrations of GuHCl.  The precise values are: 
5870   
5871            - [GuHCL][M] ln(k_a[s^-1]) k_a[s^-1] 
5872            - 0.483 0.89623903 2.4503699912708878 
5873            - 0.545 1.1694838 
5874            - 0.545 1.1761503 
5875            - 0.622 1.294 
5876            - 0.669 1.5176493 
5877            - 0.722 1.6238791 
5878            - 0.813 1.9395758 
5879            - 1.011 2.3558415 10.547000429321157 
5880          """ 
5881   
5882          # Base data setup. 
5883          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='TSMFK01', expfolder="acbp_cpmg_disp_101MGuHCl_40C_041223") 
5884   
5885          # Alias the spins. 
5886          res61L = cdp.mol[0].res[0].spin[0] 
5887   
5888          # The R20 keys. 
5889          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086270e6) 
5890   
5891          # Set the initial parameter values. 
5892          res61L.r2a = {r20_key1: 8.0} 
5893          res61L.dw = 6.5 
5894          res61L.k_AB = 11.0 
5895   
5896          # Low precision optimisation. 
5897          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5898   
5899          # Printout. 
5900          print("\n\nOptimised parameters:\n") 
5901          print("%-20s %-20s" % ("Parameter", "Value (:61)")) 
5902          print("%-20s %20.15g" % ("R2A (600 MHz)", res61L.r2a[r20_key1])) 
5903          print("%-20s %20.15g" % ("dw", res61L.dw)) 
5904          print("%-20s %20.15g" % ("k_AB", res61L.k_AB)) 
5905          print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 
5906   
5907          # Checks for residue :61. Reference values from paper 
5908   
5909          self.assertAlmostEqual(res61L.r2a[r20_key1], 8.4, 0) 
5910          self.assertAlmostEqual(res61L.dw, 6.41, 0) 
5911          self.assertAlmostEqual(res61L.k_AB, 10.55, 0) 
5912   
5913   
5914 -    def test_lm63_3site_synthetic(self): 
5915          """Test the 'LM63 3-site' dispersion model using the pure noise-free synthetic data.""" 
5916   
5917          # The path to the data files. 
5918          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'lm63_3site' 
5919   
5920          # Load the state file. 
5921          self.interpreter.reset() 
5922          self.interpreter.state.load(data_path+sep+'r2eff_values') 
5923   
5924          # A new data pipe. 
5925          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to='LM63 3-site', bundle_to='relax_disp') 
5926          self.interpreter.pipe.switch(pipe_name='LM63 3-site') 
5927   
5928          # Set up the model data. 
5929          self.interpreter.relax_disp.select_model(model='LM63 3-site') 
5930          self.interpreter.value.copy(pipe_from='R2eff - relax_disp', pipe_to='LM63 3-site', param='r2eff') 
5931          self.interpreter.spin.isotope('15N') 
5932   
5933          # Alias the spins. 
5934          spin1 = return_spin(":1") 
5935          spin2 = return_spin(":2") 
5936   
5937          # The R20 keys. 
5938          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
5939          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
5940   
5941          # Manually set the parameter values. 
5942          spin1.r2 = {r20_key1: 12.0, r20_key2: 12.0} 
5943          spin1.phi_ex_B = 0.1 
5944          spin1.phi_ex_C = 0.5 
5945          spin1.kB = 1500.0 
5946          spin1.kC = 2500.0 
5947          spin2.r2 = {r20_key1: 15.0, r20_key2: 15.0} 
5948          spin2.phi_ex_B = 0.1 
5949          spin2.phi_ex_C = 0.5 
5950          spin2.kB = 1500.0 
5951          spin2.kC = 2500.0 
5952   
5953          # Low precision optimisation. 
5954          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5955   
5956          # Monte Carlo simulations. 
5957          self.interpreter.monte_carlo.setup(number=3) 
5958          self.interpreter.monte_carlo.create_data(method='back_calc') 
5959          self.interpreter.monte_carlo.initial_values() 
5960          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-2, grad_tol=None, max_iter=10, constraints=True, scaling=True, verbosity=1) 
5961          self.interpreter.monte_carlo.error_analysis() 
5962   
5963          # Save the results. 
5964          self.interpreter.results.write(file='devnull', compress_type=1, force=True) 
5965   
5966          # The model checks. 
5967          print("\n\nOptimised parameters:\n") 
5968          print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 
5969          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 
5970          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 
5971          print("%-20s %20.15g %20.15g" % ("phi_ex_B", spin1.phi_ex_B, spin2.phi_ex_B)) 
5972          print("%-20s %20.15g %20.15g" % ("phi_ex_C", spin1.phi_ex_C, spin2.phi_ex_C)) 
5973          print("%-20s %20.15g %20.15g" % ("kB", spin1.kB, spin2.kB)) 
5974          print("%-20s %20.15g %20.15g" % ("kC", spin1.kC, spin2.kC)) 
5975          print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 
5976          self.assertAlmostEqual(spin1.r2[r20_key1], 12.0, 2) 
5977          self.assertAlmostEqual(spin1.r2[r20_key2], 12.0, 2) 
5978          self.assertAlmostEqual(spin1.phi_ex_B, 0.1, 3) 
5979          self.assertAlmostEqual(spin1.phi_ex_C, 0.5, 3) 
5980          self.assertAlmostEqual(spin1.kB/1000, 1500.0/1000, 3) 
5981          self.assertAlmostEqual(spin1.kC/1000, 2500.0/1000, 3) 
5982          self.assertAlmostEqual(spin1.chi2, 0.0, 3) 
5983          self.assertAlmostEqual(spin2.r2[r20_key1], 15.0, 3) 
5984          self.assertAlmostEqual(spin2.r2[r20_key2], 15.0, 3) 
5985          self.assertAlmostEqual(spin1.phi_ex_B, 0.1, 3) 
5986          self.assertAlmostEqual(spin1.phi_ex_C, 0.5, 3) 
5987          self.assertAlmostEqual(spin1.kB/1000, 1500.0/1000, 3) 
5988          self.assertAlmostEqual(spin1.kC/1000, 2500.0/1000, 3) 
5989          self.assertAlmostEqual(spin2.chi2, 0.0, 3) 
5990   
5991   
5992 -    def test_m61_data_to_m61(self): 
5993          """Test the relaxation dispersion 'M61' model curve fitting to fixed time synthetic data.""" 
5994   
5995          # Fixed time variable. 
5996          ds.fixed = True 
5997   
5998          # Execute the script. 
5999          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_m61.py') 
6000   
6001          # The original parameters. 
6002          i0 = [100000.0, 20000.0] 
6003          r1rho_prime = [2.25, 24.0] 
6004          pA = 0.7 
6005          kex = 1000.0 
6006          delta_omega = [1.0, 2.0] 
6007          keys = ['r1rho_800.00000000_0.000_1000.000', 'r1rho_800.00000000_0.000_1500.000', 'r1rho_800.00000000_0.000_2000.000', 'r1rho_800.00000000_0.000_2500.000', 'r1rho_800.00000000_0.000_3000.000', 'r1rho_800.00000000_0.000_3500.000', 'r1rho_800.00000000_0.000_4000.000', 'r1rho_800.00000000_0.000_4500.000', 'r1rho_800.00000000_0.000_5000.000', 'r1rho_800.00000000_0.000_5500.000', 'r1rho_800.00000000_0.000_6000.000'] 
6008          phi_ex = [] 
6009          for i in range(2): 
6010              phi_ex.append(pA * (1.0 - pA) * delta_omega[i]**2) 
6011          rates = [[3.59768160399, 2.85730469783, 2.59328084312, 2.47019857325, 2.40310451058, 2.36256876552, 2.33622716364, 2.31815271355, 2.30521680479, 2.29564174079, 2.28835686631], [29.390726416, 26.4292187913, 25.3731233725, 24.880794293, 24.6124180423, 24.4502750621, 24.3449086546, 24.2726108542, 24.2208672192, 24.1825669632, 24.1534274652]] 
6012   
6013          # Switch to the 'R2eff' model data pipe, then check for each spin. 
6014          self.interpreter.pipe.switch('R2eff - relax_disp') 
6015          spin_index = 0 
6016          for spin, spin_id in spin_loop(return_id=True): 
6017              # Printout. 
6018              print("\nSpin %s." % spin_id) 
6019   
6020              # Check the fitted parameters. 
6021              for i in range(len(keys)): 
6022                  self.assertAlmostEqual(spin.r2eff[keys[i]]/10.0, rates[spin_index][i]/10.0, 2) 
6023   
6024              # Increment the spin index. 
6025              spin_index += 1 
6026   
6027          # The R20 keys. 
6028          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
6029   
6030          # Switch to the 'M61' model data pipe, then check for each spin. 
6031          self.interpreter.pipe.switch('M61 - relax_disp') 
6032          spin_index = 0 
6033          for spin, spin_id in spin_loop(return_id=True): 
6034              # Printout. 
6035              print("\nSpin %s." % spin_id) 
6036   
6037              # Check the fitted parameters. 
6038              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index]/10, 2) 
6039              self.assertAlmostEqual(spin.phi_ex, phi_ex[spin_index], 2) 
6040              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 
6041   
6042              # Increment the spin index. 
6043              spin_index += 1 
6044   
6045   
6046 -    def test_m61_exp_data_to_m61(self): 
6047          """Test the relaxation dispersion 'M61' model curve fitting to the full exponential synthetic data.""" 
6048   
6049          # Fixed time variable. 
6050          ds.fixed = False 
6051   
6052          # Single spin optimisation. 
6053          ds.single = True 
6054   
6055          # Execute the script. 
6056          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_m61.py') 
6057   
6058          # The original parameters. 
6059          i0 = [100000.0, 20000.0] 
6060          r1rho_prime = [2.25, 24.0] 
6061          pA = 0.7 
6062          kex = 1000.0 
6063          delta_omega = [1.0, 2.0] 
6064          keys = ['r1rho_800.00000000_0.000_1000.000', 'r1rho_800.00000000_0.000_1500.000', 'r1rho_800.00000000_0.000_2000.000', 'r1rho_800.00000000_0.000_2500.000', 'r1rho_800.00000000_0.000_3000.000', 'r1rho_800.00000000_0.000_3500.000', 'r1rho_800.00000000_0.000_4000.000', 'r1rho_800.00000000_0.000_4500.000', 'r1rho_800.00000000_0.000_5000.000', 'r1rho_800.00000000_0.000_5500.000', 'r1rho_800.00000000_0.000_6000.000'] 
6065          phi_ex = [] 
6066          for i in range(2): 
6067              phi_ex.append(pA * (1.0 - pA) * delta_omega[i]**2) 
6068          rates = [[3.59768160399, 2.85730469783, 2.59328084312, 2.47019857325, 2.40310451058, 2.36256876552, 2.33622716364, 2.31815271355, 2.30521680479, 2.29564174079, 2.28835686631], [29.390726416, 26.4292187913, 25.3731233725, 24.880794293, 24.6124180423, 24.4502750621, 24.3449086546, 24.2726108542, 24.2208672192, 24.1825669632, 24.1534274652]] 
6069   
6070          # Switch to the 'R2eff' model data pipe, then check for each spin. 
6071          self.interpreter.pipe.switch('R2eff - relax_disp') 
6072          spin_index = 0 
6073          for spin, spin_id in spin_loop(return_id=True): 
6074              # Printout. 
6075              print("\nSpin %s." % spin_id) 
6076   
6077              # Check the fitted parameters. 
6078              for i in range(len(keys)): 
6079                  self.assertAlmostEqual(spin.r2eff[keys[i]]/10.0, rates[spin_index][i]/10.0, 2) 
6080   
6081              # Increment the spin index. 
6082              spin_index += 1 
6083   
6084          # The R20 keys. 
6085          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
6086   
6087          # Switch to the 'M61' model data pipe, then check for each spin. 
6088          self.interpreter.pipe.switch('M61 - relax_disp') 
6089          spin_index = 0 
6090          for spin, spin_id in spin_loop(return_id=True): 
6091              # Printout. 
6092              print("\nSpin %s." % spin_id) 
6093   
6094              # Check the fitted parameters. 
6095              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index]/10, 2) 
6096              self.assertAlmostEqual(spin.phi_ex, phi_ex[spin_index], 2) 
6097              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 
6098   
6099              # Increment the spin index. 
6100              spin_index += 1 
6101   
6102   
6103 -    def test_m61b_data_to_m61b(self): 
6104          """Test the relaxation dispersion 'M61 skew' model curve fitting to fixed time synthetic data.""" 
6105   
6106          # Execute the script. 
6107          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_m61b.py') 
6108   
6109          # The original parameters. 
6110          i0 = [100000.0, 20000.0] 
6111          r1rho_prime = [10.0, 24.0] 
6112          pA = 0.95 
6113          kex = 2000.0 
6114          delta_omega = [1.0, 2.0] 
6115   
6116          # The R20 keys. 
6117          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
6118   
6119          # Switch to the 'M61 skew' model data pipe, then check for each spin. 
6120          self.interpreter.pipe.switch("%s - relax_disp" % MODEL_M61B) 
6121          spin_index = 0 
6122          for spin, spin_id in spin_loop(return_id=True): 
6123              # Printout. 
6124              print("\nSpin %s." % spin_id) 
6125   
6126              # Check the fitted parameters. 
6127              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index]/10, 2) 
6128              self.assertAlmostEqual(spin.pA, pA, 2) 
6129              self.assertAlmostEqual(spin.dw, dw[spin_index], 2) 
6130              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 
6131   
6132              # Increment the spin index. 
6133              spin_index += 1 
6134   
6135   
6136 -    def test_model_nesting_and_param(self): 
6137          """Test that all models which can nest, have all their parameters converted.""" 
6138   
6139          # Set the experiment type. 
6140          cdp.exp_type_list = EXP_TYPE_LIST 
6141   
6142          # Get info for all models. 
6143          all_models_info = models_info(models=MODEL_LIST_FULL) 
6144   
6145          # Loop over all models. 
6146          print("Printing the listed of nested models for each model.") 
6147          print("#########################################") 
6148          for model_info in all_models_info: 
6149              print("%s"%model_info.model), 
6150              print("<-"), 
6151              nest_list = model_info.nest_list 
6152              if nest_list == None: 
6153                  nest_list = ["None"] 
6154              print(', '.join(map(str, nest_list))) 
6155   
6156              # Skip if there is no model to nest from. 
6157              if nest_list == ["None"]: 
6158                  continue 
6159   
6160              # Assign params to variable. 
6161              model_params = model_info.params 
6162   
6163              # Now loop over the nested models. 
6164              for nested_model in nest_list: 
6165                  # Get the params for the nested model. 
6166                  nested_model_params = MODEL_PARAMS[nested_model] 
6167   
6168                  # Get the dictionary of parameter conversion. 
6169                  par_dic = nesting_param(model_params=model_params, nested_model_params=nested_model_params) 
6170   
6171                  # Test the number of elements in the dictionary. 
6172                  self.assertEqual(len(par_dic), len(model_params)) 
6173   
6174                  # Loop over dictionary. 
6175                  for param in par_dic: 
6176                          if param != par_dic[param]: 
6177                              print("Model:'%s', Nested model:'%s', Copying '%s' to '%s'." % (model_info.model, nested_model, par_dic[param], param)) 
6178                          self.assertNotEqual(par_dic[param], None) 
6179   
6180   
6181 -    def test_ns_mmq_3site(self): 
6182          """Compare the 'NS MMQ 3-site' dispersion model to synthetic data from cpmg_fit.""" 
6183   
6184          # Execute the script. 
6185          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_mmq_3site.py') 
6186   
6187          # Check the chi-squared value. 
6188          self.assertAlmostEqual(cdp.mol[0].res[0].spin[1].chi2, 0.0, 3) 
6189   
6190   
6191 -    def test_ns_mmq_3site_linear(self): 
6192          """Compare the 'NS MMQ 3-site linear' dispersion model to synthetic data from cpmg_fit.""" 
6193   
6194          # Execute the script. 
6195          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_mmq_3site_linear.py') 
6196   
6197          # Check the chi-squared value. 
6198          self.assertAlmostEqual(cdp.mol[0].res[0].spin[1].chi2, 0.0, 3) 
6199   
6200   
6201 -    def test_ns_r1rho_3site(self): 
6202          """Compare the 'NS R1rho 3-site' dispersion model to synthetic data from cpmg_fit.""" 
6203   
6204          # Execute the script. 
6205          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_r1rho_3site.py') 
6206   
6207          # Check the chi-squared value. 
6208          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].chi2, 136.13141468674999, 3) 
6209   
6210   
6211 -    def test_ns_r1rho_3site_linear(self): 
6212          """Compare the 'NS R1rho 3-site linear' dispersion model to synthetic data from cpmg_fit.""" 
6213   
6214          # Execute the script. 
6215          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_r1rho_3site_linear.py') 
6216   
6217          # Check the chi-squared value. 
6218          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].chi2, 0.030959849811015544, 3) 
6219   
6220   
6221 -    def test_repeat_cpmg(self): 
6222          """Test the protocol for repeated dispersion analysis. The class: relax_disp_repeat_cpmg. 
6223   
6224          U{task #7826<https://gna.org/task/index.php?7826>}. Write an python class for the repeated analysis of dispersion data. 
6225          """ 
6226   
6227          # Reset. 
6228          self.interpreter.reset() 
6229   
6230          # Define base path to files. 
6231          base_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1' 
6232   
6233          # Setup dictionary with settings. 
6234          sdic = {} 
6235           
6236          # Spectrometer frqs in list. 
6237          sfrq_1 = 499.86214 
6238          sfrq_2 = 599.8908587 
6239          sfrqs = [sfrq_1, sfrq_2] 
6240           
6241          # Store in dictionary. 
6242          sdic['sfrqs'] = sfrqs 
6243           
6244          # Store unit for frq. 
6245          sdic['sfrq_unit'] = 'MHz' 
6246           
6247          # Store exp_type 
6248          sdic['exp_type'] = 'SQ CPMG' 
6249   
6250          # Store spin isotope 
6251          sdic['isotope'] = '15N' 
6252   
6253          # How intensity was measured. 
6254          sdic['int_method'] = 'height' 
6255   
6256          # Define the time for result directory. 
6257          sdic['time'] = '2014_09' 
6258   
6259          # Initialize frq dics. 
6260          for frq in sfrqs: 
6261              key = DIC_KEY_FORMAT % (frq) 
6262              sdic[key] = {} 
6263           
6264          # Set keys. 
6265          e_1 = DIC_KEY_FORMAT % (sfrq_1) 
6266          e_2 = DIC_KEY_FORMAT % (sfrq_2) 
6267           
6268          # Store time T2. 
6269          sdic[e_1]['time_T2'] = 0.04 
6270          sdic[e_2]['time_T2'] = 0.06 
6271           
6272          # Set ncyc. 
6273          ncyc_1 = array([20, 0, 16, 10, 36, 2, 12, 4, 22, 18, 40, 14, 26, 8, 32, 24, 6, 28, 0]) 
6274          ncyc_2 = array([28, 0, 4, 32, 60, 2, 10, 16, 8, 20, 52, 18, 40, 6, 12, 0, 24, 14, 22]) 
6275   
6276          # Calculate the cpmg_frq and store. 
6277          sdic[e_1]['cpmg_frqs'] = ncyc_1 / sdic[e_1]['time_T2'] 
6278          sdic[e_2]['cpmg_frqs'] = ncyc_2 / sdic[e_2]['time_T2'] 
6279           
6280          # Define peak lists. 
6281          peaks_folder_1 = base_path +sep+ 'cpmg_disp_sod1d90a_060518' +sep+ 'cpmg_disp_sod1d90a_060518_normal.fid' +sep+ 'analysis_FT' +sep+ 'ser_files' 
6282          peaks_folder_2 = base_path +sep+ 'cpmg_disp_sod1d90a_060521' +sep+ 'cpmg_disp_sod1d90a_060521_normal.fid' +sep+ 'analysis_FT' +sep+ 'ser_files'  
6283          sdic[e_1]['peaks_folder'] = peaks_folder_1 
6284          sdic[e_2]['peaks_folder'] = peaks_folder_2 
6285           
6286          # Define folder to all rmsd files. 
6287          rmsd_folder_1 = base_path +sep+ 'cpmg_disp_sod1d90a_060518' +sep+ 'cpmg_disp_sod1d90a_060518_normal.fid' +sep+ 'ft2_data' 
6288          rmsd_folder_2 = base_path +sep+ 'cpmg_disp_sod1d90a_060521' +sep+ 'cpmg_disp_sod1d90a_060521_normal.fid' +sep+ 'ft2_data' 
6289          sdic[e_1]['rmsd_folder'] = rmsd_folder_1  
6290          sdic[e_2]['rmsd_folder'] = rmsd_folder_2 
6291   
6292          # Define temporary folder. 
6293          sdic['results_dir'] = self.tmpdir 
6294   
6295          # Setup class with data. 
6296          RDR =  Relax_disp_rep(sdic) 
6297   
6298          # Setup base information. 
6299          RDR.set_base_cpmg(method='FT', glob_ini=128) 
6300   
6301          methods = ['FT', 'MDD'] 
6302          #methods = ['FT'] 
6303   
6304          # Set the intensity. 
6305          #RDR.set_int(methods=methods, list_glob_ini=[128, 126], set_rmsd=False, set_rep=True) 
6306          #RDR.set_int(methods=methods, list_glob_ini=[128, 126], set_rmsd=True, set_rep=False) 
6307   
6308          # Try plot some intensity correlations. 
6309          if True: 
6310              selection = None 
6311   
6312              # Now make a spin selection. 
6313              int_ft_sel = RDR.col_int(method='FT', list_glob_ini=[128, 126], selection=selection) 
6314   
6315              # For mdd 
6316              int_mdd_sel = RDR.col_int(method='MDD', list_glob_ini=[128, 126], selection=selection) 
6317   
6318              # Plot correlation of intensity 
6319              fig1 = [[int_ft_sel, int_mdd_sel], ['FT', 'MDD'], [128, 128]] 
6320              fig2 = [[int_ft_sel, int_mdd_sel], ['FT', 'MDD'], [128, 126]] 
6321              corr_data = [fig1, fig2] 
6322   
6323              write_stats = True 
6324              RDR.plot_int_corr(corr_data=corr_data, show=False, write_stats=write_stats) 
6325   
6326              # Open stat file. 
6327              if write_stats: 
6328                  for i, corr_data_i in enumerate(corr_data): 
6329                      data, methods, glob_inis = corr_data[i] 
6330                      data_x, data_y = data 
6331                      method_x, method_y = methods 
6332                      glob_ini_x, glob_ini_y = glob_inis 
6333                      x = data_x[str(glob_ini_x)]['peak_intensity_arr'] 
6334                      np = len(x) 
6335   
6336                      file_name_ini = 'int_corr_%s_%s_%s_%s_NP_%i' % (method_x, glob_ini_x, method_y, glob_ini_y, np) 
6337   
6338                      if selection == None: 
6339                          file_name = file_name_ini + '_all.txt' 
6340                      else: 
6341                          file_name = file_name_ini + '_sel.txt' 
6342                      path = RDR.results_dir 
6343                      data = extract_data(file=file_name, dir=path) 
6344   
6345                      # Loop over the lines. 
6346                      for i, data_i in enumerate(data): 
6347                          print(i, data_i) 
6348   
6349   
6350          # Try plot some intensity statistics. 
6351          if True: 
6352              # Collect r2eff values. 
6353              selections = [None, ':2,3'] 
6354              for selection in selections: 
6355                  int_ft_sel = RDR.col_int(method='FT', list_glob_ini=[128], selection=selection) 
6356                  int_mdd_sel = RDR.col_int(method='MDD', list_glob_ini=[128, 126], selection=selection) 
6357   
6358                  # Get R2eff stats. 
6359                  int_stat_dic = RDR.get_int_stat_dic(list_int_dics=[int_ft_sel, int_mdd_sel], list_glob_ini=[128, 126]) 
6360   
6361                  ## Plot R2eff stats 
6362                  write_stats = True 
6363                  RDR.plot_int_stat(int_stat_dic=int_stat_dic, methods=['FT', 'MDD'], list_glob_ini=[128, 126], show=False, write_stats=write_stats) 
6364   
6365                  # Open stat file. 
6366                  if write_stats: 
6367                      if selection == None: 
6368                          file_name = 'int_stat_all.txt' 
6369                      else: 
6370                          file_name = 'int_stat_sel.txt' 
6371                      path = RDR.results_dir 
6372                      data = extract_data(file=file_name, dir=path) 
6373   
6374                      # Loop over the lines. 
6375                      for i, data_i in enumerate(data): 
6376                          print(i, data_i) 
6377   
6378   
6379          # Try write some R2eff correlations. 
6380          if True: 
6381              selection = None 
6382              # Collect r2eff values. 
6383              r2eff_ft_all = RDR.col_r2eff(method='FT', list_glob_ini=[128, 126, 6], selection=selection) 
6384   
6385              # For all spins, mdd 
6386              r2eff_mdd_all = RDR.col_r2eff(method='MDD', list_glob_ini=[128, 126], selection=selection) 
6387   
6388              # Plot correlation of intensity 
6389              fig1 = [[r2eff_ft_all, r2eff_mdd_all], ['FT', 'MDD'], [128, 128]] 
6390              fig2 = [[r2eff_ft_all, r2eff_mdd_all], ['FT', 'MDD'], [128, 126]] 
6391              corr_data = [fig1, fig2] 
6392   
6393              write_stats = True 
6394              RDR.plot_r2eff_corr(corr_data=corr_data, show=False, write_stats=write_stats) 
6395   
6396              # Open stat file. 
6397              if write_stats: 
6398                  for i, corr_data_i in enumerate(corr_data): 
6399                      data, methods, glob_inis = corr_data[i] 
6400                      data_x, data_y = data 
6401                      method_x, method_y = methods 
6402                      glob_ini_x, glob_ini_y = glob_inis 
6403                      x = data_x[str(glob_ini_x)]['r2eff_arr'] 
6404                      np = len(x) 
6405   
6406                      file_name_ini = 'r2eff_corr_%s_%s_%s_%s_NP_%i' % (method_x, glob_ini_x, method_y, glob_ini_y, np) 
6407   
6408                      if selection == None: 
6409                          file_name = file_name_ini + '_all.txt' 
6410                      else: 
6411                          file_name = file_name_ini + '_sel.txt' 
6412                      path = RDR.results_dir 
6413                      data = extract_data(file=file_name, dir=path) 
6414   
6415                      # Loop over the lines. 
6416                      for i, data_i in enumerate(data): 
6417                          print(i, data_i) 
6418   
6419   
6420          # Try plot some R2eff statistics. 
6421          if True: 
6422              # Collect r2eff values. 
6423              selections = [None, ':2,3'] 
6424              for selection in selections: 
6425                  r2eff_ft_sel = RDR.col_r2eff(method='FT', list_glob_ini=[128, 126, 6], selection=selection) 
6426                  r2eff_mdd_sel = RDR.col_r2eff(method='MDD', list_glob_ini=[128, 126], selection=selection) 
6427   
6428                  # Get R2eff stats. 
6429                  r2eff_stat_dic = RDR.get_r2eff_stat_dic(list_r2eff_dics=[r2eff_ft_sel, r2eff_mdd_sel], list_glob_ini=[128, 126]) 
6430   
6431                  ## Plot R2eff stats 
6432                  write_stats = True 
6433                  RDR.plot_r2eff_stat(r2eff_stat_dic=r2eff_stat_dic, methods=['FT', 'MDD'], list_glob_ini=[128, 126, 6], show=False, write_stats=write_stats) 
6434   
6435                  # Open stat file. 
6436                  if write_stats: 
6437                      if selection == None: 
6438                          file_name = 'r2eff_stat_all.txt' 
6439                      else: 
6440                          file_name = 'r2eff_stat_sel.txt' 
6441                      path = RDR.results_dir 
6442                      data = extract_data(file=file_name, dir=path) 
6443   
6444                      # Loop over the lines. 
6445                      for i, data_i in enumerate(data): 
6446                          print(i, data_i) 
6447   
6448   
6449          # Do minimisation individual. 
6450          if True: 
6451              methods = ['FT', 'MDD'] 
6452              # Now calculate R2eff. 
6453              RDR.calc_r2eff(methods=methods, list_glob_ini=[128, 126]) 
6454   
6455              min_methods = [['FT'], ['MDD']] 
6456              min_list_glob_ini = [[128], list(range(126, 130, 2))[::-1]] 
6457   
6458              #min_methods = [['FT']] 
6459              #min_list_glob_ini = [[128]] 
6460              #selection = ':2,3' 
6461              selection = None 
6462   
6463              for i, methods in enumerate(min_methods): 
6464                  list_glob_ini = min_list_glob_ini[i] 
6465   
6466                  if True: 
6467                      # First get data. 
6468                      if True: 
6469                          # First load all data. 
6470                          RDR.calc_r2eff(methods=methods, list_glob_ini=list_glob_ini) 
6471   
6472                      # Then set R20 
6473                      if True: 
6474                          # Set R20 from min R2eff in preparation for Grid search. 
6475                          RDR.r20_from_min_r2eff(methods=methods, model=MODEL_CR72, model_from=MODEL_R2EFF, analysis='grid_setup_ind', analysis_from='int', list_glob_ini=list_glob_ini, force=True) 
6476   
6477                      # Check and print parameters. 
6478                      if True: 
6479                          # Print for pipe name 
6480                          method = methods[0] 
6481                          glob_ini = list_glob_ini[0] 
6482   
6483                          test_pipe_name = RDR.name_pipe(method=method, model=MODEL_CR72, analysis='grid_setup_ind', glob_ini=glob_ini) 
6484                          RDR.spin_display_params(pipe_name=test_pipe_name) 
6485   
6486                      # Then Grid search. 
6487                      if True: 
6488                          # Do Grid search. 
6489                          RDR.minimise_grid_search(inc=4, verbosity=1, methods=methods, model=MODEL_CR72, analysis='grid_setup_ind', list_glob_ini=list_glob_ini, force=True) 
6490   
6491                  # Then Minimise. 
6492                  if True: 
6493                      # Minimise 
6494                      RDR.opt_max_iterations = int(1e2) 
6495                      RDR.minimise_execute(methods=methods, model=MODEL_CR72, analysis='min_ind', analysis_from='grid_setup_ind', list_glob_ini=list_glob_ini, force=True) 
6496   
6497                  #print asd 
6498   
6499          # Plot statistics. 
6500          # Try plot some minimisation correlations. 
6501          if True: 
6502              selections = [None, ':2,3'] 
6503              for selection in selections: 
6504                  # Collect param values. 
6505                  analysis = 'min_ind' 
6506                  min_ft_sel = RDR.col_min(method='FT', model=MODEL_CR72, analysis=analysis, list_glob_ini=[128], selection=selection) 
6507                  min_mdd_sel = RDR.col_min(method='MDD', model=MODEL_CR72, analysis=analysis, list_glob_ini=list(range(126, 130, 2))[::-1], selection=selection) 
6508   
6509                  fig1 = [[min_ft_sel, min_mdd_sel], ['FT', 'MDD'], [128, 128]] 
6510                  fig2 = [[min_ft_sel, min_mdd_sel], ['FT', 'MDD'], [128, 126]] 
6511                  corr_data = [fig1, fig2] 
6512   
6513                  write_stats = True 
6514                  RDR.plot_min_corr(corr_data=corr_data, show=False, write_stats=write_stats) 
6515   
6516                  # Open stat file. 
6517                  if write_stats: 
6518                      for i, corr_data_i in enumerate(corr_data): 
6519                          data, methods, glob_inis = corr_data[i] 
6520                          data_x, data_y = data 
6521                          method_x, method_y = methods 
6522                          glob_ini_x, glob_ini_y = glob_inis 
6523   
6524                          file_name_ini = '%s_%s_%s_%s_%s' % (analysis, method_x, glob_ini_x, method_y, glob_ini_y) 
6525   
6526                          if selection == None: 
6527                              file_name = file_name_ini + '_all.txt' 
6528                          else: 
6529                              file_name = file_name_ini + '_sel.txt' 
6530                          path = RDR.results_dir 
6531                          data = extract_data(file=file_name, dir=path) 
6532   
6533                          # Loop over the lines. 
6534                          for i, data_i in enumerate(data): 
6535                              print(i, data_i) 
6536   
6537          # Try plot some minimisation statistics. 
6538          if True: 
6539              # Collect param values. 
6540              #selections = [None, ':2,3'] 
6541              selections = [None, ':2,3'] 
6542              for selection in selections: 
6543                  analysis = 'min_ind' 
6544                  min_ft_sel = RDR.col_min(method='FT', model=MODEL_CR72, analysis=analysis, list_glob_ini=[128], selection=selection) 
6545                  min_mdd_sel = RDR.col_min(method='MDD', model=MODEL_CR72, analysis=analysis, list_glob_ini=list(range(126, 130, 2))[::-1], selection=selection) 
6546   
6547                  # Get param stats. 
6548                  min_stat_dic = RDR.get_min_stat_dic(list_r2eff_dics=[min_ft_sel, min_mdd_sel], list_glob_ini=[128, 126]) 
6549   
6550                  ## Plot R2eff stats 
6551                  write_stats = True 
6552                  RDR.plot_min_stat(min_stat_dic=min_stat_dic, methods=['FT', 'MDD'], list_glob_ini=[128, 126, 6], show=False, write_stats=write_stats) 
6553   
6554                  # Open stat file. 
6555                  if write_stats: 
6556                      if selection == None: 
6557                          file_name = '%s_stat_all.txt' % (analysis) 
6558                      else: 
6559                          file_name = '%s_stat_sel.txt' % (analysis) 
6560                      path = RDR.results_dir 
6561                      data = extract_data(file=file_name, dir=path) 
6562   
6563                      # Loop over the lines. 
6564                      for i, data_i in enumerate(data): 
6565                          print(i, data_i) 
6566   
6567   
6568          # Do minimisation clustered. 
6569          if True: 
6570              methods = ['FT', 'MDD'] 
6571              # Now calculate R2eff. 
6572              RDR.calc_r2eff(methods=methods, list_glob_ini=[128, 126]) 
6573   
6574              min_methods = [['FT'], ['MDD']] 
6575              min_list_glob_ini = [[128], list(range(126, 130, 2))[::-1]] 
6576   
6577              #min_methods = [['FT']] 
6578              #min_list_glob_ini = [[128]] 
6579              selection = ':2,3' 
6580   
6581              for i, methods in enumerate(min_methods): 
6582                  list_glob_ini = min_list_glob_ini[i] 
6583   
6584                  if True: 
6585                      # First get data. 
6586                      if True: 
6587                          # First load all data. 
6588                          RDR.calc_r2eff(methods=methods, list_glob_ini=list_glob_ini) 
6589                       
6590                      # Then select spins. 
6591                      if True: 
6592                          # Deselect all spins. 
6593                          RDR.deselect_all(methods=methods, model='setup', model_from=MODEL_R2EFF, analysis='grid_setup', analysis_from='int', list_glob_ini=list_glob_ini, force=True) 
6594                   
6595                          RDR.select_spin(spin_id=selection, methods=methods, model='setup', analysis='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6596                   
6597                      # Then preset values. 
6598                      if True: 
6599                          # Set k_AB for Grid search. 
6600                          RDR.value_set(methods=methods, val=1000., param='kex', model=MODEL_CR72, model_from='setup', analysis='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6601                          RDR.value_set(methods=methods, val=0.95, param='pA', model=MODEL_CR72, model_from='setup', analysis='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6602                   
6603                      # Then set R20 
6604                      if True: 
6605                          # Set R20 from min R2eff in preparation for Grid search. 
6606                          RDR.r20_from_min_r2eff(methods=methods, model=MODEL_CR72, analysis='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6607                   
6608                      # Check and print parameters. 
6609                      if True: 
6610                          # Print for pipe name 
6611                          method = methods[0] 
6612                          glob_ini = list_glob_ini[0] 
6613   
6614                          test_pipe_name = RDR.name_pipe(method=method, model=MODEL_CR72, analysis='grid_setup', glob_ini=glob_ini) 
6615                          RDR.spin_display_params(pipe_name=test_pipe_name) 
6616                       
6617                      # Then Grid search. 
6618                      if True: 
6619                          # Do Grid search. 
6620                          RDR.minimise_grid_search(inc=200, verbosity=1, methods=methods, model=MODEL_CR72, analysis='grid', analysis_from='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6621                   
6622                      # Then cluster spins. 
6623                      if True: 
6624                          RDR.cluster_spins(spin_id=selection, methods=methods, model=MODEL_CR72, analysis='grid', list_glob_ini=list_glob_ini, force=True) 
6625               
6626                  # Then Minimise. 
6627                  if True: 
6628                      # Minimise 
6629                      RDR.opt_max_iterations = int(1e2) 
6630                      RDR.minimise_execute(methods=methods, model=MODEL_CR72, analysis='min', analysis_from='grid', list_glob_ini=list_glob_ini, force=False) 
6631   
6632          # Plot statistics. 
6633          # Try plot some minimisation correlations. 
6634          if True: 
6635              selection = ':2,3' 
6636              # Collect param values. 
6637              analysis = 'min' 
6638              min_ft_sel = RDR.col_min(method='FT', model=MODEL_CR72, analysis=analysis, list_glob_ini=[128], selection=selection) 
6639              min_mdd_sel = RDR.col_min(method='MDD', model=MODEL_CR72, analysis=analysis, list_glob_ini=list(range(126, 130, 2))[::-1], selection=selection) 
6640   
6641              fig1 = [[min_ft_sel, min_mdd_sel], ['FT', 'MDD'], [128, 128]] 
6642              fig2 = [[min_ft_sel, min_mdd_sel], ['FT', 'MDD'], [128, 126]] 
6643              corr_data = [fig1, fig2] 
6644   
6645              write_stats = True 
6646              RDR.plot_min_corr(corr_data=corr_data, show=False, write_stats=write_stats) 
6647   
6648              # Open stat file. 
6649              if write_stats: 
6650                  for i, corr_data_i in enumerate(corr_data): 
6651                      data, methods, glob_inis = corr_data[i] 
6652                      data_x, data_y = data 
6653                      method_x, method_y = methods 
6654                      glob_ini_x, glob_ini_y = glob_inis 
6655   
6656                      file_name_ini = '%s_%s_%s_%s_%s' % (analysis, method_x, glob_ini_x, method_y, glob_ini_y) 
6657   
6658                      if selection == None: 
6659                          file_name = file_name_ini + '_all.txt' 
6660                      else: 
6661                          file_name = file_name_ini + '_sel.txt' 
6662                      path = RDR.results_dir 
6663                      data = extract_data(file=file_name, dir=path) 
6664   
6665                      # Loop over the lines. 
6666                      for i, data_i in enumerate(data): 
6667                          print(i, data_i) 
6668   
6669          # Try plot some minimisation statistics. 
6670          if True: 
6671              # Collect param values. 
6672              selections = [':2,3'] 
6673              for selection in selections: 
6674                  analysis = 'min' 
6675                  min_ft_sel = RDR.col_min(method='FT', model=MODEL_CR72, analysis=analysis, list_glob_ini=[128], selection=selection) 
6676                  min_mdd_sel = RDR.col_min(method='MDD', model=MODEL_CR72, analysis=analysis, list_glob_ini=list(range(126, 130, 2))[::-1], selection=selection) 
6677   
6678                  # Get param stats. 
6679                  min_stat_dic = RDR.get_min_stat_dic(list_r2eff_dics=[min_ft_sel, min_mdd_sel], list_glob_ini=[128, 126]) 
6680   
6681                  ## Plot R2eff stats 
6682                  write_stats = True 
6683                  RDR.plot_min_stat(min_stat_dic=min_stat_dic, methods=['FT', 'MDD'], list_glob_ini=[128, 126, 6], show=False, write_stats=write_stats) 
6684   
6685                  # Open stat file. 
6686                  if write_stats: 
6687                      if selection == None: 
6688                          file_name = '%s_stat_all.txt' % (analysis) 
6689                      else: 
6690                          file_name = '%s_stat_sel.txt' % (analysis) 
6691                      path = RDR.results_dir 
6692                      data = extract_data(file=file_name, dir=path) 
6693   
6694                      # Loop over the lines. 
6695                      for i, data_i in enumerate(data): 
6696                          print(i, data_i) 
6697   
6698   
6699   
6700 -    def test_r1rho_kjaergaard_auto(self): 
6701          """Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
6702   
6703          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
6704   
6705          This uses the automatic analysis. 
6706   
6707          """ 
6708   
6709          # Cluster residues 
6710          cluster_ids = [ 
6711          ":13@N", 
6712          ":15@N", 
6713          ":16@N", 
6714          ":25@N", 
6715          ":26@N", 
6716          ":28@N", 
6717          ":39@N", 
6718          ":40@N", 
6719          ":41@N", 
6720          ":43@N", 
6721          ":44@N", 
6722          ":45@N", 
6723          ":49@N", 
6724          ":52@N", 
6725          ":53@N"] 
6726   
6727          # Load the data. 
6728          self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids) 
6729   
6730          # Test some of the sequence. 
6731          self.assertEqual(len(cdp.mol), 1) 
6732          self.assertEqual(cdp.mol[0].name, None) 
6733          self.assertEqual(len(cdp.mol[0].res), 48) 
6734   
6735          # Test the chemical shift data. 
6736          cs = [122.223, 122.162, 114.250, 125.852, 118.626, 117.449, 119.999, 122.610, 118.602, 118.291, 115.393, 
6737          121.288, 117.448, 116.378, 116.316, 117.263, 122.211, 118.748, 118.103, 119.421, 119.317, 119.386, 117.279, 
6738          122.103, 120.038, 116.698, 111.811, 118.639, 118.285, 121.318, 117.770, 119.948, 119.759, 118.314, 118.160, 
6739          121.442, 118.714, 113.080, 125.706, 119.183, 120.966, 122.361, 126.675, 117.069, 120.875, 109.372, 119.811, 126.048] 
6740   
6741          i = 0 
6742          for spin, spin_id in spin_loop(return_id=True): 
6743              # Check the chemical shift. 
6744              self.assertEqual(spin.chemical_shift, cs[i]) 
6745   
6746              # Increment the index. 
6747              i += 1 
6748   
6749          # Initialize counter 
6750          i = 0 
6751          j = 0 
6752          # Count instances of select/deselect 
6753          for curspin, mol_name, res_num, res_name, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=False): 
6754              if curspin.select == True: 
6755                  i += 1 
6756              if curspin.select == False: 
6757                  j += 1 
6758   
6759          # Test number of selected/deselected spins. 
6760          self.assertEqual(i, len(cluster_ids)) 
6761          self.assertEqual(j, 48-len(cluster_ids)) 
6762   
6763          # Check the initial setup. 
6764          self.assertEqual(cdp.mol[0].res[7].num, 13) 
6765          self.assertEqual(cdp.mol[0].res[7].spin[0].kex, ds.guess[':13@N'][6]) 
6766          self.assertEqual(cdp.mol[0].res[7].spin[0].ri_data['R1'], ds.ref[':13@N'][2]) 
6767   
6768          self.assertEqual(cdp.mol[0].res[9].num, 15) 
6769          self.assertEqual(cdp.mol[0].res[9].spin[0].kex, ds.guess[':15@N'][6]) 
6770          self.assertEqual(cdp.mol[0].res[9].spin[0].ri_data['R1'], ds.ref[':15@N'][2]) 
6771   
6772          self.assertEqual(cdp.mol[0].res[10].num, 16) 
6773          self.assertEqual(cdp.mol[0].res[10].spin[0].kex, ds.guess[':16@N'][6]) 
6774          self.assert_(hasattr(cdp.mol[0].res[10].spin[0], 'ri_data')) 
6775   
6776          self.assertEqual(cdp.mol[0].res[16].num, 25) 
6777          self.assertEqual(cdp.mol[0].res[16].spin[0].kex, ds.guess[':25@N'][6]) 
6778          self.assert_(hasattr(cdp.mol[0].res[16].spin[0], 'ri_data')) 
6779   
6780          self.assertEqual(cdp.mol[0].res[17].num, 26) 
6781          self.assertEqual(cdp.mol[0].res[17].spin[0].kex, ds.guess[':26@N'][6]) 
6782          self.assert_(hasattr(cdp.mol[0].res[17].spin[0], 'ri_data')) 
6783   
6784          self.assertEqual(cdp.mol[0].res[19].num, 28) 
6785          self.assertEqual(cdp.mol[0].res[19].spin[0].kex, ds.guess[':28@N'][6]) 
6786          self.assert_(hasattr(cdp.mol[0].res[19].spin[0], 'ri_data')) 
6787   
6788          self.assertEqual(cdp.mol[0].res[29].num, 39) 
6789          self.assertEqual(cdp.mol[0].res[29].spin[0].kex, ds.guess[':39@N'][6]) 
6790          self.assert_(hasattr(cdp.mol[0].res[29].spin[0], 'ri_data')) 
6791   
6792          self.assertEqual(cdp.mol[0].res[30].num, 40) 
6793          self.assertEqual(cdp.mol[0].res[30].spin[0].kex, ds.guess[':40@N'][6]) 
6794          self.assert_(hasattr(cdp.mol[0].res[30].spin[0], 'ri_data')) 
6795   
6796          self.assertEqual(cdp.mol[0].res[31].num, 41) 
6797          self.assertEqual(cdp.mol[0].res[31].spin[0].kex, ds.guess[':41@N'][6]) 
6798          self.assert_(hasattr(cdp.mol[0].res[31].spin[0], 'ri_data')) 
6799   
6800          self.assertEqual(cdp.mol[0].res[33].num, 43) 
6801          self.assertEqual(cdp.mol[0].res[33].spin[0].kex, ds.guess[':43@N'][6]) 
6802          self.assert_(hasattr(cdp.mol[0].res[33].spin[0], 'ri_data')) 
6803   
6804          self.assertEqual(cdp.mol[0].res[34].num, 44) 
6805          self.assertEqual(cdp.mol[0].res[34].spin[0].kex, ds.guess[':44@N'][6]) 
6806          self.assert_(hasattr(cdp.mol[0].res[34].spin[0], 'ri_data')) 
6807   
6808          self.assertEqual(cdp.mol[0].res[35].num, 45) 
6809          self.assertEqual(cdp.mol[0].res[35].spin[0].kex, ds.guess[':45@N'][6]) 
6810          self.assert_(hasattr(cdp.mol[0].res[35].spin[0], 'ri_data')) 
6811   
6812          self.assertEqual(cdp.mol[0].res[38].num, 49) 
6813          self.assertEqual(cdp.mol[0].res[38].spin[0].kex, ds.guess[':49@N'][6]) 
6814          self.assert_(hasattr(cdp.mol[0].res[38].spin[0], 'ri_data')) 
6815   
6816          self.assertEqual(cdp.mol[0].res[41].num, 52) 
6817          self.assertEqual(cdp.mol[0].res[41].spin[0].kex, ds.guess[':52@N'][6]) 
6818          self.assert_(hasattr(cdp.mol[0].res[41].spin[0], 'ri_data')) 
6819   
6820          self.assertEqual(cdp.mol[0].res[42].num, 53) 
6821          self.assertEqual(cdp.mol[0].res[42].spin[0].kex, ds.guess[':53@N'][6]) 
6822          self.assert_(hasattr(cdp.mol[0].res[42].spin[0], 'ri_data')) 
6823   
6824          # The dispersion models. 
6825          MODELS = [MODEL_R2EFF, MODEL_NOREX, MODEL_DPL94, MODEL_TP02, MODEL_TAP03, MODEL_MP05, MODEL_NS_R1RHO_2SITE] 
6826   
6827          # The grid search size (the number of increments per dimension). 
6828          GRID_INC = 4 
6829   
6830          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
6831          MC_NUM = 3 
6832   
6833          # Model selection technique. 
6834          MODSEL = 'AIC' 
6835   
6836          # Execute the auto-analysis (fast). 
6837          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
6838          OPT_FUNC_TOL = 1e-1 
6839          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
6840          OPT_MAX_ITERATIONS = 1000 
6841          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
6842   
6843          result_dir_name = ds.tmpdir 
6844   
6845          # Make all spins free 
6846          for curspin in cluster_ids: 
6847              self.interpreter.relax_disp.cluster('free spins', curspin) 
6848              # Shut them down 
6849              self.interpreter.deselect.spin(spin_id=curspin, change_all=False) 
6850   
6851          # Select only a subset of spins for global fitting 
6852          #self.interpreter.select.spin(spin_id=':41@N', change_all=False) 
6853          #self.interpreter.relax_disp.cluster('model_cluster', ':41@N') 
6854   
6855          #self.interpreter.select.spin(spin_id=':40@N', change_all=False) 
6856          #self.interpreter.relax_disp.cluster('model_cluster', ':40@N') 
6857   
6858          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
6859          #self.interpreter.relax_disp.cluster('model_cluster', ':52@N') 
6860   
6861          # Run the analysis. 
6862          relax_disp.Relax_disp(pipe_name=ds.pipe_name, pipe_bundle=ds.pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL) 
6863   
6864          # Check the kex value of residue 52 
6865          #self.assertAlmostEqual(cdp.mol[0].res[41].spin[0].kex, ds.ref[':52@N'][6]) 
6866   
6867          # Print results for each model. 
6868          print("\n\n################") 
6869          print("Printing results") 
6870          print("################\n") 
6871          for model in MODELS: 
6872              # Skip R2eff model. 
6873              if model == MODEL_R2EFF: 
6874                  continue 
6875   
6876              # Switch to pipe. 
6877              self.interpreter.pipe.switch(pipe_name='%s - relax_disp' % (model)) 
6878              print("\nModel: %s" % (model)) 
6879   
6880              # Loop over the spins. 
6881              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
6882                  # Generate spin string. 
6883                  spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
6884   
6885                  # Loop over the parameters. 
6886                  print("Optimised parameters for spin: %s" % (spin_string)) 
6887                  for param in cur_spin.params + ['chi2']: 
6888                      # Get the value. 
6889                      if param in ['r1', 'r2']: 
6890                          for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True): 
6891                              # Generate the R20 key. 
6892                              r20_key = generate_r20_key(exp_type=exp_type, frq=frq) 
6893   
6894                              # Get the value. 
6895                              value = getattr(cur_spin, param)[r20_key] 
6896   
6897                              # Print value. 
6898                              print("%-10s %-6s %-6s %3.3f" % ("Parameter:", param, "Value:", value)) 
6899   
6900                      # For all other parameters. 
6901                      else: 
6902                          # Get the value. 
6903                          value = getattr(cur_spin, param) 
6904   
6905                          # Print value. 
6906                          print("%-10s %-6s %-6s %3.3f" % ("Parameter:", param, "Value:", value)) 
6907   
6908          # Print the final pipe. 
6909          self.interpreter.pipe.switch(pipe_name='%s - relax_disp' % ('final')) 
6910          print("\nFinal pipe") 
6911   
6912   
6913 -    def test_r1rho_kjaergaard_auto_check_graphs(self): 
6914          """Check of plot_disp_curves() function, after optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'R2eff' model. 
6915   
6916          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
6917   
6918          This uses the automatic analysis. 
6919   
6920          """ 
6921   
6922          # Cluster residues 
6923          cluster_ids = [ 
6924          ":52@N"] 
6925   
6926          # Load the data. 
6927          self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids) 
6928   
6929          # The dispersion models. 
6930          MODELS = [MODEL_R2EFF] 
6931   
6932          # The grid search size (the number of increments per dimension). 
6933          GRID_INC = 4 
6934   
6935          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
6936          MC_NUM = 3 
6937   
6938          # Model selection technique. 
6939          MODSEL = 'AIC' 
6940   
6941          # Execute the auto-analysis (fast). 
6942          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
6943          OPT_FUNC_TOL = 1e-1 
6944          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
6945          OPT_MAX_ITERATIONS = 1000 
6946          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
6947   
6948          result_dir_name = ds.tmpdir 
6949   
6950          # Make all spins free 
6951          for curspin in cluster_ids: 
6952              self.interpreter.relax_disp.cluster('free spins', curspin) 
6953              # Shut them down 
6954              self.interpreter.deselect.spin(spin_id=curspin, change_all=False) 
6955   
6956          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
6957   
6958          # Run the analysis. 
6959          relax_disp.Relax_disp(pipe_name=ds.pipe_name, pipe_bundle=ds.pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL) 
6960   
6961          # Check the graphs produced. 
6962          graph_comb = [ 
6963          [Y_AXIS_R2_EFF, X_AXIS_DISP, INTERPOLATE_DISP], 
6964          [Y_AXIS_R2_EFF, X_AXIS_THETA, INTERPOLATE_DISP], 
6965          [Y_AXIS_R2_R1RHO, X_AXIS_W_EFF, INTERPOLATE_DISP], 
6966          [Y_AXIS_R2_EFF, X_AXIS_THETA, INTERPOLATE_OFFSET] 
6967          ] 
6968   
6969          # Define expected folder names. 
6970          result_folders = MODELS 
6971   
6972          # Assign spin_id. 
6973          spin_id = ':52@N' 
6974   
6975          # Loop over result folders. 
6976          for result_folder in result_folders: 
6977              # Skip the model R2eff, which does not produce graphs. 
6978              if result_folder == MODEL_R2EFF: 
6979                  continue 
6980   
6981              # Loop over graphs. 
6982              for y_axis, x_axis, interpolate in graph_comb: 
6983                  # Determine file name: 
6984                  file_name_ini = return_grace_file_name_ini(y_axis=y_axis, x_axis=x_axis, interpolate=interpolate) 
6985   
6986                  # Make the file name. 
6987                  file_name = "%s%s.agr" % (file_name_ini, spin_id.replace('#', '_').replace(':', '_').replace('@', '_')) 
6988   
6989                  # Get the file path. 
6990                  file_path = get_file_path(file_name, result_dir_name+sep+result_folder) 
6991   
6992                  print("Testing file access to graph: %s"%file_path) 
6993                  self.assert_(access(file_path, F_OK)) 
6994   
6995          # Start testing all possible combinations of graphs. 
6996          y_axis_types = [Y_AXIS_R2_EFF, Y_AXIS_R2_R1RHO] 
6997          x_axis_types = [X_AXIS_DISP, X_AXIS_THETA, X_AXIS_W_EFF] 
6998          interpolate_types = [INTERPOLATE_DISP, INTERPOLATE_OFFSET] 
6999   
7000          result_dir_name = ds.tmpdir 
7001   
7002          # Loop through all possible combinations of y_axis, x_axis and interpolation. 
7003          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013'+sep+'check_graphs' 
7004   
7005          for result_folder in result_folders: 
7006              # Skip the model R2eff, which does not produce graphs. 
7007              if result_folder == MODEL_R2EFF: 
7008                  continue 
7009   
7010              for y_axis in y_axis_types: 
7011                  for x_axis in x_axis_types: 
7012                      for interpolate in interpolate_types: 
7013                          # Determine file name: 
7014                          file_name_ini = return_grace_file_name_ini(y_axis=y_axis, x_axis=x_axis, interpolate=interpolate) 
7015   
7016                          # Make the file name. 
7017                          file_name = "%s%s.agr" % (file_name_ini, spin_id.replace('#', '_').replace(':', '_').replace('@', '_')) 
7018   
7019                          # Write the curves. 
7020                          dir = result_dir_name+sep+result_folder 
7021                          print("Plotting combination of %s, %s, %s"%(y_axis, x_axis, interpolate)) 
7022                          self.interpreter.relax_disp.plot_disp_curves(dir=dir, y_axis=y_axis, x_axis=x_axis, interpolate=interpolate, force=True) 
7023   
7024                          # Get the file path. 
7025                          file_path = get_file_path(file_name, dir) 
7026   
7027                          # Test the plot file exists. 
7028                          print("Testing file access to graph: %s"%file_path) 
7029                          self.assert_(access(file_path, F_OK)) 
7030   
7031                          # Now open, and compare content, line by line. 
7032                          file_prod = open(file_path) 
7033                          lines_prod = file_prod.readlines() 
7034                          file_prod.close() 
7035   
7036                          # Define file to compare against. 
7037                          dir_comp = data_path+sep+result_folder 
7038                          file_path_comp = get_file_path(file_name, dir_comp) 
7039                          file_comp = open(file_path_comp) 
7040                          lines_comp = file_comp.readlines() 
7041                          file_comp.close() 
7042   
7043                          # Assert number of lines is equal. 
7044                          self.assertEqual(len(lines_prod), len(lines_comp)) 
7045                          for j in range(len(lines_prod)): 
7046                              # Make the string test 
7047                              first_char = lines_prod[j][0] 
7048                              if first_char in ["@", "&"]: 
7049                                  self.assertEqual(lines_prod[j], lines_comp[j]) 
7050                              else: 
7051                                  # Split string in x, y, error. 
7052                                  # The error would change per run. 
7053                                  x_prod, y_prod, y_prod_err = lines_prod[j].split() 
7054                                  x_comp, y_comp, y_comp_err = lines_comp[j].split() 
7055                                  self.assertAlmostEqual(float(x_prod), float(x_comp)) 
7056                                  self.assertAlmostEqual(float(y_prod), float(y_comp)) 
7057   
7058   
7059 -    def test_r1rho_kjaergaard_missing_r1(self): 
7060          """Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
7061   
7062          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
7063   
7064          This uses the automatic analysis, with missing loading R1. 
7065   
7066          """ 
7067   
7068          # Cluster residues 
7069          cluster_ids = [ 
7070          ":13@N", 
7071          ":15@N", 
7072          ":16@N", 
7073          ":25@N", 
7074          ":26@N", 
7075          ":28@N", 
7076          ":39@N", 
7077          ":40@N", 
7078          ":41@N", 
7079          ":43@N", 
7080          ":44@N", 
7081          ":45@N", 
7082          ":49@N", 
7083          ":52@N", 
7084          ":53@N"] 
7085   
7086          # Load the data. 
7087          self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids, read_R1=False) 
7088   
7089          # The dispersion models. 
7090          MODELS = [MODEL_R2EFF, MODEL_NOREX, MODEL_DPL94, MODEL_TP02, MODEL_TAP03, MODEL_MP05, MODEL_NS_R1RHO_2SITE] 
7091   
7092          # The grid search size (the number of increments per dimension). 
7093          GRID_INC = None 
7094   
7095          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
7096          MC_NUM = 3 
7097   
7098          # Model selection technique. 
7099          MODSEL = 'AIC' 
7100   
7101          # Execute the auto-analysis (fast). 
7102          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
7103          OPT_FUNC_TOL = 1e-25 
7104          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
7105          OPT_MAX_ITERATIONS = 10000000 
7106          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
7107   
7108          result_dir_name = ds.tmpdir 
7109   
7110          # Make all spins free 
7111          for curspin in cluster_ids: 
7112              self.interpreter.relax_disp.cluster('free spins', curspin) 
7113              # Shut them down 
7114              self.interpreter.deselect.spin(spin_id=curspin, change_all=False) 
7115   
7116          # Select only a subset of spins for global fitting 
7117          #self.interpreter.select.spin(spin_id=':41@N', change_all=False) 
7118          #self.interpreter.relax_disp.cluster('model_cluster', ':41@N') 
7119   
7120          #self.interpreter.select.spin(spin_id=':40@N', change_all=False) 
7121          #self.interpreter.relax_disp.cluster('model_cluster', ':40@N') 
7122   
7123          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
7124          #self.interpreter.relax_disp.cluster('model_cluster', ':52@N') 
7125   
7126          # Point to directory with R2eff values, with 2000 MC simulations. 
7127          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' +sep+ "check_graphs" +sep+ "mc_2000" 
7128   
7129          r1_fit = True 
7130   
7131          # Run the analysis. 
7132          relax_disp.Relax_disp(pipe_name=ds.pipe_name, pipe_bundle=ds.pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL, pre_run_dir=prev_data_path, r1_fit=r1_fit) 
7133   
7134          # Verify the data. 
7135          self.verify_r1rho_kjaergaard_missing_r1(models=MODELS, result_dir_name=result_dir_name, r2eff_estimate='MC2000') 
7136   
7137   
7138 -    def test_r2eff_read(self): 
7139          """Test the operation of the relax_disp.r2eff_read user function.""" 
7140   
7141          # The path to the data files. 
7142          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen'+sep+'800_MHz' 
7143   
7144          # Read the sequence data. 
7145          self.interpreter.sequence.read(file='66.667.in', dir=data_path, res_num_col=1) 
7146   
7147          # The ID. 
7148          id = 'test' 
7149   
7150          # Set up the metadata. 
7151          self.interpreter.spectrometer.frequency(id=id, frq=800e6) 
7152          self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 
7153   
7154          # Try reading the file. 
7155          self.interpreter.relax_disp.r2eff_read(id=id, file='66.667.in', dir=data_path, disp_frq=66.667, res_num_col=1, data_col=2, error_col=3) 
7156   
7157          # Check the global data. 
7158          data = [ 
7159              ['cpmg_frqs', {'test': 66.667}], 
7160              ['cpmg_frqs_list', [66.667]], 
7161              ['dispersion_points', 1], 
7162              ['exp_type', {'test': 'SQ CPMG'}], 
7163              ['exp_type_list', ['SQ CPMG']], 
7164              ['spectrometer_frq', {'test': 800000000.0}], 
7165              ['spectrometer_frq_count', 1], 
7166              ['spectrometer_frq_list', [800000000.0]], 
7167              ['spectrum_ids', ['test']] 
7168          ] 
7169          for name, value in data: 
7170              # Does it exist? 
7171              self.assert_(hasattr(cdp, name)) 
7172   
7173              # Check the object. 
7174              obj = getattr(cdp, name) 
7175              self.assertEqual(obj, value) 
7176   
7177          # Check the spin data. 
7178          data = [ 
7179              [1,       2.3035747e+04, 8.5467725e+01], 
7180              [2,       9.9629762e+04, 2.8322033e+02], 
7181              [3,       9.5663137e+04, 2.8632929e+02], 
7182              [4,       1.7089893e+05, 3.1089428e+02], 
7183              [5,       4.7323876e+04, 1.0084269e+02], 
7184              [6,       2.0199122e+04, 1.0135220e+02], 
7185              [7,       1.6655488e+05, 3.1609061e+02], 
7186              [8,       9.0061074e+04, 1.9176585e+02], 
7187              [10,      8.4726204e+04, 2.8898155e+02], 
7188              [11,      1.5050233e+05, 4.3138029e+02], 
7189              [12,      9.2998531e+04, 3.0440191e+02], 
7190              [13,      1.6343507e+05, 3.3144097e+02], 
7191              [14,      1.0137301e+05, 3.7314642e+02], 
7192              [15,      8.3407837e+04, 1.6546473e+02], 
7193              [16,      1.3819126e+05, 3.3388517e+02], 
7194              [17,      1.1010490e+05, 3.5639222e+02], 
7195              [18,      9.4324035e+04, 3.2343585e+02], 
7196              [19,      1.1135179e+05, 3.0706671e+02], 
7197              [20,      7.6339410e+04, 1.7377460e+02], 
7198              [21,      6.2008453e+04, 1.7327150e+02], 
7199              [22,      1.0590404e+05, 2.4814635e+02], 
7200              [23,      1.0630198e+05, 2.3601100e+02], 
7201              [24,      7.2996320e+04, 1.4952465e+02], 
7202              [25,      9.5486742e+04, 2.7080766e+02], 
7203              [26,      5.8067989e+04, 1.6820462e+02], 
7204              [27,     -1.7168510e+04, 2.2519560e+02], 
7205              [28,      1.6891473e+05, 2.3497525e+02], 
7206              [29,      9.4038555e+04, 2.0357593e+02], 
7207              [30,      2.1386951e+04, 2.2153532e+02], 
7208              [31,      9.3982899e+04, 2.0937056e+02], 
7209              [32,      8.6097484e+04, 2.3868467e+02], 
7210              [33,      1.0194337e+05, 2.7370704e+02], 
7211              [34,      8.5683111e+04, 2.0838076e+02], 
7212              [35,      8.6985768e+04, 2.0889310e+02], 
7213              [36,      8.6011237e+04, 1.7498390e+02], 
7214              [37,      1.0984097e+05, 2.7622998e+02], 
7215              [38,      8.7017879e+04, 2.6547994e+02], 
7216              [39,      9.1682649e+04, 5.2777676e+02], 
7217              [40,      7.6370440e+04, 1.9873214e+02], 
7218              [41,      9.1393531e+04, 2.4483824e+02], 
7219              [42,      1.1017111e+05, 2.8020699e+02], 
7220              [43,      9.4552366e+04, 3.4394150e+02], 
7221              [44,      1.2858281e+05, 6.8449252e+02], 
7222              [45,      7.4583525e+04, 1.9544210e+02], 
7223              [46,      9.2087490e+04, 2.0491066e+02], 
7224              [47,      9.7507255e+04, 2.5162839e+02], 
7225              [48,      1.0033842e+05, 2.7566430e+02], 
7226              [49,      1.3048305e+05, 2.6797466e+02], 
7227              [50,      1.0546796e+05, 1.9304384e+02], 
7228              [51,      9.3099697e+04, 2.0773311e+02], 
7229              [52,      4.6863758e+04, 1.3169068e+02], 
7230              [53,      6.1055806e+04, 1.5448477e+02], 
7231              [55,      6.8629994e+04, 1.6868673e+02], 
7232              [56,      1.1005552e+05, 2.1940465e+02], 
7233              [57,      1.0572760e+05, 1.9768486e+02], 
7234              [58,      1.1176950e+05, 3.0009610e+02], 
7235              [59,      9.8758603e+04, 3.3803895e+02], 
7236              [60,      9.9517201e+04, 3.5137994e+02], 
7237              [61,      5.4357946e+04, 2.5896579e+02], 
7238              [62,      1.0899978e+05, 2.8720371e+02], 
7239              [63,      8.4549759e+04, 4.1401837e+02], 
7240              [64,      5.5014550e+04, 2.1135781e+02], 
7241              [65,      8.0569666e+04, 2.3249709e+02], 
7242              [66,      1.2936610e+05, 3.5218725e+02], 
7243              [67,      3.6438010e+04, 8.7924003e+01], 
7244              [70,      3.8763157e+04, 1.3325040e+02], 
7245              [71,      8.5711411e+04, 2.9316183e+02], 
7246              [72,      3.3211541e+04, 1.2182123e+02], 
7247              [73,      3.2070576e+04, 1.2305430e+02] 
7248          ] 
7249          for res_num, value, error in data: 
7250              # Get the spin. 
7251              spin = return_spin(spin_id=":%s"%res_num) 
7252   
7253              # Check the values. 
7254              self.assertEqual(spin.r2eff['sq_cpmg_800.00000000_0.000_66.667'], value) 
7255              self.assertEqual(spin.r2eff_err['sq_cpmg_800.00000000_0.000_66.667'], error) 
7256   
7257   
7258 -    def test_r2eff_read_spin(self): 
7259          """Test the operation of the relax_disp.r2eff_read_spin user function.""" 
7260   
7261          # The path to the data files. 
7262          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Korzhnev_et_al_2005' 
7263   
7264          # Generate the sequence. 
7265          self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='H') 
7266          self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='N') 
7267          self.interpreter.spin.isotope('1H', spin_id='@H') 
7268          self.interpreter.spin.isotope('15N', spin_id='@N') 
7269   
7270          # Build the experiment IDs. 
7271          H_disp_points = [67.0, 133.0, 267.0, 400.0, 533.0, 667.0, 800.0, 933.0, 1067.0, 1600.0, 2133.0, 2667.0] 
7272          N_disp_points = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 500.0, 600.0, 700.0, 800.0, 900.0, 1000.0] 
7273          ids = [] 
7274          for value in H_disp_points: 
7275              ids.append('1H_CPMG_%s' % value) 
7276          for value in N_disp_points: 
7277              ids.append('15N_CPMG_%s' % value) 
7278          print("\n\nThe experiment IDs are %s." % ids) 
7279   
7280          # Set up the metadata for the experiments. 
7281          for id in ids: 
7282              self.interpreter.spectrometer.frequency(id=id, frq=500e6) 
7283              self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 
7284          for value in H_disp_points: 
7285              self.interpreter.relax_disp.cpmg_setup(spectrum_id='1H_CPMG_%s' % value, cpmg_frq=value) 
7286          for value in N_disp_points: 
7287              self.interpreter.relax_disp.cpmg_setup(spectrum_id='15N_CPMG_%s' % value, cpmg_frq=value) 
7288   
7289          # Loop over the experiments. 
7290          for id, file, spin_id in [['1H_CPMG', 'hs_500.res', ':9@H'], ['15N_CPMG', 'ns_500.res', ':9@N']]: 
7291              # Try reading the file. 
7292              self.interpreter.relax_disp.r2eff_read_spin(id=id, file=file, dir=data_path, spin_id=spin_id, disp_point_col=1, data_col=2, error_col=3) 
7293   
7294          # Check the global data. 
7295          data = [ 
7296              ['cpmg_frqs', {'1H_CPMG_667.0': 667.0, '1H_CPMG_1067.0': 1067.0, '15N_CPMG_350.0': 350.0, '1H_CPMG_933.0': 933.0, '15N_CPMG_50.0': 50.0, '15N_CPMG_100.0': 100.0, '1H_CPMG_400.0': 400.0, '1H_CPMG_533.0': 533.0, '1H_CPMG_800.0': 800.0, '15N_CPMG_900.0': 900.0, '15N_CPMG_150.0': 150.0, '15N_CPMG_800.0': 800.0, '1H_CPMG_267.0': 267.0, '1H_CPMG_2667.0': 2667.0, '15N_CPMG_300.0': 300.0, '1H_CPMG_133.0': 133.0, '15N_CPMG_700.0': 700.0, '1H_CPMG_67.0': 67.0, '15N_CPMG_400.0': 400.0, '15N_CPMG_250.0': 250.0, '1H_CPMG_2133.0': 2133.0, '1H_CPMG_1600.0': 1600.0, '15N_CPMG_200.0': 200.0, '15N_CPMG_1000.0': 1000.0, '15N_CPMG_500.0': 500.0, '15N_CPMG_600.0': 600.0}], 
7297              ['cpmg_frqs_list', [50.0, 67.0, 100.0, 133.0, 150.0, 200.0, 250.0, 267.0, 300.0, 350.0, 400.0, 500.0, 533.0, 600.0, 667.0, 700.0, 800.0, 900.0, 933.0, 1000.0, 1067.0, 1600.0, 2133.0, 2667.0]], 
7298              ['dispersion_points', 24], 
7299              ['exp_type', {'1H_CPMG_667.0': 'SQ CPMG', '1H_CPMG_1067.0': 'SQ CPMG', '15N_CPMG_350.0': 'SQ CPMG', '1H_CPMG_933.0': 'SQ CPMG', '15N_CPMG_50.0': 'SQ CPMG', '15N_CPMG_100.0': 'SQ CPMG', '1H_CPMG_400.0': 'SQ CPMG', '1H_CPMG_533.0': 'SQ CPMG', '1H_CPMG_800.0': 'SQ CPMG', '15N_CPMG_900.0': 'SQ CPMG', '15N_CPMG_150.0': 'SQ CPMG', '15N_CPMG_800.0': 'SQ CPMG', '1H_CPMG_267.0': 'SQ CPMG', '1H_CPMG_2667.0': 'SQ CPMG', '15N_CPMG_300.0': 'SQ CPMG', '1H_CPMG_133.0': 'SQ CPMG', '15N_CPMG_700.0': 'SQ CPMG', '1H_CPMG_67.0': 'SQ CPMG', '15N_CPMG_400.0': 'SQ CPMG', '15N_CPMG_250.0': 'SQ CPMG', '1H_CPMG_2133.0': 'SQ CPMG', '1H_CPMG_1600.0': 'SQ CPMG', '15N_CPMG_200.0': 'SQ CPMG', '15N_CPMG_1000.0': 'SQ CPMG', '15N_CPMG_500.0': 'SQ CPMG', '15N_CPMG_600.0': 'SQ CPMG'}], 
7300              ['exp_type_list', ['SQ CPMG']], 
7301              ['spectrometer_frq', {'1H_CPMG_667.0': 500000000.0, '1H_CPMG_1067.0': 500000000.0, '15N_CPMG_350.0': 500000000.0, '1H_CPMG_933.0': 500000000.0, '15N_CPMG_50.0': 500000000.0, '15N_CPMG_100.0': 500000000.0, '1H_CPMG_400.0': 500000000.0, '1H_CPMG_533.0': 500000000.0, '1H_CPMG_800.0': 500000000.0, '15N_CPMG_900.0': 500000000.0, '15N_CPMG_150.0': 500000000.0, '15N_CPMG_800.0': 500000000.0, '1H_CPMG_267.0': 500000000.0, '1H_CPMG_2667.0': 500000000.0, '15N_CPMG_300.0': 500000000.0, '1H_CPMG_133.0': 500000000.0, '15N_CPMG_700.0': 500000000.0, '1H_CPMG_67.0': 500000000.0, '15N_CPMG_400.0': 500000000.0, '15N_CPMG_250.0': 500000000.0, '1H_CPMG_2133.0': 500000000.0, '1H_CPMG_1600.0': 500000000.0, '15N_CPMG_200.0': 500000000.0, '15N_CPMG_1000.0': 500000000.0, '15N_CPMG_500.0': 500000000.0, '15N_CPMG_600.0': 500000000.0}], 
7302              ['spectrometer_frq_count', 1], 
7303              ['spectrometer_frq_list', [500000000.0]], 
7304              ['spectrum_ids', ['1H_CPMG_67.0', '1H_CPMG_133.0', '1H_CPMG_267.0', '1H_CPMG_400.0', '1H_CPMG_533.0', '1H_CPMG_667.0', '1H_CPMG_800.0', '1H_CPMG_933.0', '1H_CPMG_1067.0', '1H_CPMG_1600.0', '1H_CPMG_2133.0', '1H_CPMG_2667.0', '15N_CPMG_50.0', '15N_CPMG_100.0', '15N_CPMG_150.0', '15N_CPMG_200.0', '15N_CPMG_250.0', '15N_CPMG_300.0', '15N_CPMG_350.0', '15N_CPMG_400.0', '15N_CPMG_500.0', '15N_CPMG_600.0', '15N_CPMG_700.0', '15N_CPMG_800.0', '15N_CPMG_900.0', '15N_CPMG_1000.0']] 
7305          ] 
7306          for name, value in data: 
7307              # Does it exist? 
7308              self.assert_(hasattr(cdp, name)) 
7309   
7310              # Check the object. 
7311              obj = getattr(cdp, name) 
7312              if not isinstance(data, dict): 
7313                  self.assertEqual(obj, value) 
7314   
7315              # Check the global dictionary data. 
7316              else: 
7317                  for id in ids: 
7318                      self.assertEqual(obj[id], value[id]) 
7319   
7320          # Check the spin data. 
7321          h_data = [ 
7322              [  67.0,  21.47924,   0.42958], 
7323              [ 133.0,  16.73898,   0.33478], 
7324              [ 267.0,   9.97357,   0.19947], 
7325              [ 400.0,   8.23877,   0.24737], 
7326              [ 533.0,   7.59290,   0.24263], 
7327              [ 667.0,   7.45843,   0.24165], 
7328              [ 800.0,   7.11222,   0.23915], 
7329              [ 933.0,   7.40880,   0.24129], 
7330              [1067.0,   6.55191,   0.16629], 
7331              [1600.0,   6.72177,   0.23637], 
7332              [2133.0,   7.09629,   0.23904], 
7333              [2667.0,   7.14675,   0.23940] 
7334          ] 
7335          for disp_point, value, error in h_data: 
7336              id = 'sq_cpmg_500.00000000_0.000_%.3f' % disp_point 
7337              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff[id], value) 
7338              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff_err[id], error) 
7339          n_data = [ 
7340              [  50.0,  27.15767,   0.54315], 
7341              [ 100.0,  26.55781,   0.53116], 
7342              [ 150.0,  24.73462,   0.49469], 
7343              [ 200.0,  20.98617,   0.41972], 
7344              [ 250.0,  17.82442,   0.35649], 
7345              [ 300.0,  15.55352,   0.31107], 
7346              [ 350.0,  13.78958,   0.27579], 
7347              [ 400.0,  12.48334,   0.24967], 
7348              [ 500.0,  11.55724,   0.23114], 
7349              [ 600.0,  10.53874,   0.21077], 
7350              [ 700.0,  10.07395,   0.20148], 
7351              [ 800.0,   9.62952,   0.19259], 
7352              [ 900.0,   9.49994,   0.19000], 
7353              [1000.0,   8.71350,   0.17427] 
7354          ] 
7355          for disp_point, value, error in n_data: 
7356              id = 'sq_cpmg_500.00000000_0.000_%.3f' % disp_point 
7357              self.assertEqual(cdp.mol[0].res[0].spin[1].r2eff[id], value) 
7358              self.assertEqual(cdp.mol[0].res[0].spin[1].r2eff_err[id], error) 
7359   
7360   
7361 -    def test_r2eff_fit_fixed_time(self): 
7362          """Test the relaxation dispersion 'R2eff' model for fixed time data in the auto-analysis.""" 
7363   
7364          # Execute the script. 
7365          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r2eff_calc.py') 
7366   
7367   
7368 -    def test_read_r2eff(self): 
7369          """Test the reading of a file containing r2eff values.""" 
7370   
7371          # Create the sequence data, and name the spins. 
7372          self.interpreter.residue.create(1, 'Gly') 
7373          self.interpreter.residue.create(2, 'Gly') 
7374          self.interpreter.residue.create(3, 'Gly') 
7375   
7376          # Read the file. 
7377          self.interpreter.relax_data.read(ri_id='R2eff.600', ri_type='R2eff', frq=600*1e6, file='r2eff.out', dir=status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r2eff', res_num_col=1, res_name_col=2, data_col=3, error_col=4) 
7378   
7379          # Test the data. 
7380          self.assertEqual(cdp.mol[0].res[0].spin[0].ri_data['R2eff.600'], 15.000) 
7381          self.assertEqual(cdp.mol[0].res[1].spin[0].ri_data['R2eff.600'], 4.2003) 
7382          self.assertEqual(cdp.mol[0].res[2].spin[0].ri_data['R2eff.600'], 7.2385) 
7383   
7384   
7385 -    def test_r20_from_min_r2eff_cpmg(self): 
7386          """Test speeding up grid search. Support requst sr #3151 U{https://gna.org/support/index.php?3151}. 
7387   
7388          User function to set the R20 parameters in the default grid search using the minimum R2eff value. 
7389   
7390          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
7391          'SOD1-WT' CPMG data to the CR72 dispersion model. 
7392   
7393          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
7394          Data is for experiment at 25 degree Celcius. 
7395          """ 
7396   
7397          # Base data setup. 
7398          pipe_name = 'base pipe' 
7399          pipe_type = 'relax_disp' 
7400          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
7401          select_spin_index = list(range(0, 1)) 
7402          self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 
7403   
7404          # Generate r20 key. 
7405          r20_key_600 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.8908617*1E6) 
7406          r20_key_500 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=499.862139*1E6) 
7407   
7408          ## Now prepare for MODEL calculation. 
7409          MODEL = "CR72" 
7410   
7411          # Change pipe. 
7412          pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 
7413          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
7414          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
7415   
7416          # Then select model. 
7417          self.interpreter.relax_disp.select_model(model=MODEL) 
7418   
7419          # Set the R20 parameters in the default grid search using the minimum R2eff value. 
7420          self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
7421   
7422          # Test result, for normal run. 
7423          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7424              # Get the spin_params. 
7425              spin_params = spin.params 
7426   
7427              # Defined fixed values for testing. 
7428              if spin_id == ":10@N": 
7429                  self.assertEqual(spin.r2[r20_key_600], 20.282732526087106) 
7430                  self.assertEqual(spin.r2[r20_key_500], 18.475299724356649) 
7431   
7432              # Print out. 
7433              print("r2_600=%2.2f r2_500=%2.2f spin_id=%s resi=%i resn=%s"%(spin.r2[r20_key_600], spin.r2[r20_key_500], spin_id, resi, resn)) 
7434   
7435              # Testing the r2 values for the different fields are not the same. 
7436              self.assert_(spin.r2[r20_key_600] != spin.r2[r20_key_500]) 
7437   
7438              # Test values are larger than 0. 
7439              self.assert_(spin.r2[r20_key_600] > 0.0) 
7440              self.assert_(spin.r2[r20_key_500] > 0.0) 
7441   
7442              # Loop over the experiment settings. 
7443              r2eff_600 = [] 
7444              r2eff_500 = [] 
7445              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
7446                  # Create the data key. 
7447                  data_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
7448   
7449                  # Extract the r2 eff data. 
7450                  r2eff = spin.r2eff[data_key] 
7451                  if frq == 599.8908617*1E6: 
7452                      r2eff_600.append(r2eff) 
7453                  elif frq == 499.862139*1E6: 
7454                      r2eff_500.append(r2eff) 
7455   
7456              # Sort values. 
7457              r2eff_600.sort() 
7458              r2eff_500.sort() 
7459   
7460              # Test values again. 
7461              print("For r20 600MHz min r2eff=%3.3f."%(min(r2eff_600))) 
7462              print(r2eff_600) 
7463              self.assertEqual(spin.r2[r20_key_600], min(r2eff_600)) 
7464              print("") 
7465   
7466              print("For r20 500MHz min r2eff=%3.3f."%(min(r2eff_500))) 
7467              print(r2eff_500) 
7468              self.assertEqual(spin.r2[r20_key_500], min(r2eff_500)) 
7469              print("") 
7470   
7471          print("###########################################") 
7472          print("Trying GRID SEARCH for minimum R2eff values") 
7473   
7474          ### Test just the Grid search. 
7475          GRID_INC = 5 
7476   
7477          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID_INC, constraints=True, verbosity=1) 
7478   
7479          ### Then test the value.set function. 
7480          # Change pipe. 
7481          pipe_name_MODEL = "%s_%s_2"%(pipe_name, MODEL) 
7482          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
7483          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
7484   
7485          # Then select model. 
7486          self.interpreter.relax_disp.select_model(model=MODEL) 
7487   
7488          # Then set the standard parameter values. 
7489          for param in spin_params: 
7490              print("Setting standard parameter for param: %s"%param) 
7491              self.interpreter.value.set(param=param, index=None) 
7492   
7493          # Test result, for normal run. 
7494          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7495              # Print out. 
7496              print("r2_600=%2.2f r2_500=%2.2f pA=%2.2f, dw=%2.2f, kex=%2.2f, spin_id=%s resi=%i resn=%s"%(spin.r2[r20_key_600], spin.r2[r20_key_500], spin.pA, spin.dw, spin.kex, spin_id, resi, resn)) 
7497   
7498              # Testing the r2 values. 
7499              self.assertEqual(spin.r2[r20_key_600], 10.00) 
7500              self.assertEqual(spin.r2[r20_key_500], 10.00) 
7501              self.assertEqual(spin.pA, 0.9) 
7502              self.assertEqual(spin.dw, 1.0) 
7503              self.assertEqual(spin.kex, 1000.0) 
7504   
7505          print("###########################################") 
7506          print("Trying GRID SEARCH for standard R2eff values") 
7507   
7508          ### Test just the Grid search. 
7509          GRID_INC = 5 
7510   
7511          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID_INC, constraints=True, verbosity=1) 
7512   
7513          ### Run auto_analysis. 
7514          # The grid search size (the number of increments per dimension). 
7515          GRID_INC = 5 
7516   
7517          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
7518          MC_NUM = 3 
7519   
7520          # Model selection technique. 
7521          MODSEL = 'AIC' 
7522   
7523          # Execute the auto-analysis (fast). 
7524          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
7525          OPT_FUNC_TOL = 1e-1 
7526          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
7527          OPT_MAX_ITERATIONS = 1000 
7528          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
7529   
7530          # Run the analysis. 
7531          relax_disp.Relax_disp(pipe_name=pipe_name_r2eff, results_dir=ds.tmpdir, models=[MODEL], grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL, set_grid_r20=True) 
7532   
7533   
7534 -    def test_show_apod_extract(self): 
7535          """Test getting the spectrum noise for spectrum fourier transformed with NMRPipe, and tool showApod.""" 
7536   
7537          # The path to the data files. 
7538          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1'+sep+'cpmg_disp_sod1d90a_060518'+sep+'cpmg_disp_sod1d90a_060518_normal.fid'+sep+'ft2_data' 
7539   
7540          # Define file name. 
7541          file_name = '128_0_FT.ft2' 
7542   
7543          # Call function. 
7544          get_output = show_apod_extract(file_name=file_name, dir=data_path) 
7545   
7546          # Define how output should look like. 
7547          # The output from showApod differs slightly according to NMRPipe version. But 'Noise Std Dev' is the same. 
7548          # Dont test lines which can differ. 
7549          show_apod_ver = [ 
7550              'REMARK Effect of Processing on Peak Parameters and Noise for %s'%(data_path+sep+file_name), 
7551              'REMARK Automated Noise Std Dev in Processed Data: 8583.41', 
7552              'REMARK Noise Std Dev Before Processing H1 and N15: 60.6558', 
7553              '', 
7554              'VARS   AXIS LABEL  TSIZE FSIZE LW_ADJ LW_FINAL HI_FACTOR VOL_FACTOR SIGMA_FACTOR', 
7555              'FORMAT %s   %-8s   %4d   %4d   %7.4f  %7.4f    %.4e      %.4e       %.4e'] 
7556              #'', 
7557              #'       X    H1       800  2048 0.8107 3.7310   4.9903e-03 9.8043e-04 5.2684e-02', 
7558              #'       Y    N15      128   256 0.7303 3.0331   3.1260e-02 7.8434e-03 1.3413e-01'] 
7559   
7560          for i, line in enumerate(show_apod_ver): 
7561              line_ver = get_output[i] 
7562   
7563              print(line) 
7564              if line[:50] == 'REMARK Noise Std Dev Before Processing H1 and N15:': 
7565                  continue 
7566              # Make the string test 
7567              self.assertEqual(line, line_ver) 
7568   
7569   
7570 -    def test_show_apod_rmsd(self): 
7571          """Test getting the spectrum noise for spectrum fourier transformed with NMRPipe, and tool showApod.""" 
7572   
7573          # The path to the data files. 
7574          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1'+sep+'cpmg_disp_sod1d90a_060518'+sep+'cpmg_disp_sod1d90a_060518_normal.fid'+sep+'ft2_data' 
7575   
7576          # Define file name. 
7577          file_name = '128_0_FT.ft2' 
7578   
7579          # Call function. 
7580          rmsd = show_apod_rmsd(file_name=file_name, dir=data_path) 
7581   
7582          # Assert. 
7583          self.assertEqual(rmsd, 8583.41) 
7584   
7585   
7586 -    def test_show_apod_rmsd_dir_to_files(self): 
7587          """Test searching for all NMRPipe spectrum files in dir, call showApod, and write to files.""" 
7588   
7589          # The path to the data files. 
7590          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1'+sep+'cpmg_disp_sod1d90a_060518'+sep+'cpmg_disp_sod1d90a_060518_normal.fid'+sep+'ft2_data' 
7591   
7592          # Call function, and get all file names. 
7593          wfile_paths = show_apod_rmsd_dir_to_files(file_ext='.ft2', dir=data_path, outdir=self.tmpdir) 
7594   
7595          # Loop over file_paths. 
7596          for wfile_path in wfile_paths: 
7597              # Open the file. 
7598              get_data = extract_data(file=wfile_path) 
7599   
7600              # Extract line 0, column 0. 
7601              test = float(get_data[0][0]) 
7602   
7603              # Assert. 
7604              self.assertEqual(test, 8583.41) 
7605   
7606   
7607 -    def test_show_apod_rmsd_to_file(self): 
7608          """Test getting the spectrum noise for spectrum fourier transformed with NMRPipe, and tool showApod, and write to file.""" 
7609   
7610          # The path to the data files. 
7611          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1'+sep+'cpmg_disp_sod1d90a_060518'+sep+'cpmg_disp_sod1d90a_060518_normal.fid'+sep+'ft2_data' 
7612   
7613          # Define file name. 
7614          file_name = '128_0_FT.ft2' 
7615   
7616          # Call function, and get file name. 
7617          wfile_path = show_apod_rmsd_to_file(file_name=file_name, dir=data_path, outdir=self.tmpdir) 
7618   
7619          # Open the file. 
7620          get_data = extract_data(file=wfile_path) 
7621   
7622          # Extract line 0, column 0. 
7623          test = float(get_data[0][0]) 
7624   
7625          # Assert. 
7626          self.assertEqual(test, 8583.41) 
7627   
7628   
7629 -    def test_sod1wt_t25_bug_21954_order_error_analysis(self): 
7630          """Error analysis of SOD1-WT CPMG. From paper at U{http://dx.doi.org/10.1073/pnas.0907387106}. 
7631   
7632          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
7633          'SOD1-WT' CPMG data to the CR72 dispersion model. 
7634   
7635          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
7636          Data is for experiment at 25 degree Celcius. 
7637   
7638          bug #21954 U{https://gna.org/bugs/index.php?21954}: Order of spectrum.error_analysis is important. 
7639          """ 
7640   
7641          # Base data setup. 
7642          pipe_name = 'base pipe' 
7643          pipe_type = 'relax_disp' 
7644          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
7645          select_spin_index = list(range(0, 1)) 
7646          self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 
7647   
7648          # Define replicated 
7649          repl_A = ['Z_A1', 'Z_A15'] 
7650          repl_B = ['Z_B1', 'Z_B18'] 
7651   
7652          # Loop over spectrum ID, and sort them 
7653          spectrum_ids_A = [] 
7654          spectrum_ids_B = [] 
7655          for spectrum_id in cdp.spectrum_ids: 
7656              if "A" in spectrum_id: 
7657                  spectrum_ids_A.append(spectrum_id) 
7658              elif "B" in spectrum_id: 
7659                  spectrum_ids_B.append(spectrum_id) 
7660   
7661          # To clean up old error analysis, delete attributes 
7662          delattr(cdp, "var_I") 
7663          delattr(cdp, "sigma_I") 
7664   
7665          # Perform error analysis 
7666          self.interpreter.spectrum.error_analysis(subset=spectrum_ids_A) 
7667          self.interpreter.spectrum.error_analysis(subset=spectrum_ids_B) 
7668   
7669          # Loop over spins, save errors to list 
7670          Errors_A_B = [] 
7671          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7672              A_err = spin.peak_intensity_err[spectrum_ids_A[0]] 
7673              B_err = spin.peak_intensity_err[spectrum_ids_B[0]] 
7674              Errors_A_B.append([A_err, B_err]) 
7675   
7676          # To clean up old error analysis, delete attributes 
7677          delattr(cdp, "var_I") 
7678          delattr(cdp, "sigma_I") 
7679   
7680          # Perform error analysis. Order is important 
7681          self.interpreter.spectrum.error_analysis(subset=spectrum_ids_B) 
7682          self.interpreter.spectrum.error_analysis(subset=spectrum_ids_A) 
7683   
7684          # Loop over spins, save errors to list 
7685          Errors_B_A = [] 
7686          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7687              A_err = spin.peak_intensity_err[spectrum_ids_A[0]] 
7688              B_err = spin.peak_intensity_err[spectrum_ids_B[0]] 
7689              Errors_B_A.append([A_err, B_err]) 
7690   
7691          # Make test for order of error 
7692          for i in range(len(Errors_A_B)): 
7693              Error_A_B = Errors_A_B[i] 
7694              Error_B_A = Errors_B_A[i] 
7695              self.assertAlmostEqual(Error_A_B[0], Error_B_A[0], 4) 
7696              self.assertAlmostEqual(Error_A_B[1], Error_B_A[1], 4) 
7697   
7698          # Make further tests for fixed values 
7699          std_A = math.sqrt((cdp.var_I[repl_A[0]] + cdp.var_I[repl_A[1]])/2) 
7700          std_A_fix = 2785.7263335738567 
7701   
7702          for id_A in spectrum_ids_A: 
7703              self.assertEqual(cdp.sigma_I[id_A], std_A) 
7704              self.assertAlmostEqual(cdp.sigma_I[id_A], std_A_fix, 7) 
7705   
7706          std_B = math.sqrt((cdp.var_I[repl_B[0]] + cdp.var_I[repl_B[1]])/2) 
7707          std_B_fix = 4967.3772030667988 
7708   
7709          for id_B in spectrum_ids_B: 
7710              self.assertEqual(cdp.sigma_I[id_B], std_B) 
7711              self.assertAlmostEqual(cdp.sigma_I[id_B], std_B_fix, 7) 
7712   
7713   
7714 -    def test_sod1wt_t25_to_cr72(self): 
7715          """Optimisation of SOD1-WT CPMG. From paper at U{http://dx.doi.org/10.1073/pnas.0907387106}. 
7716   
7717          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
7718          'SOD1-WT' CPMG data to the CR72 dispersion model. 
7719   
7720          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
7721          Data is for experiment at 25 degree Celcius. 
7722          """ 
7723   
7724          # Base data setup. 
7725          pipe_name = 'base pipe' 
7726          pipe_type = 'relax_disp' 
7727          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
7728          select_spin_index = list(range(0, 2)) 
7729          self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 
7730   
7731          # Generate r20 key. 
7732          r20_key_600 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.8908617*1E6) 
7733          r20_key_500 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=499.862139*1E6) 
7734   
7735          ## Now prepare for MODEL calculation. 
7736          MODEL = "CR72" 
7737   
7738          # Change pipe. 
7739          pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 
7740          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
7741          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
7742   
7743          # Then select model. 
7744          self.interpreter.relax_disp.select_model(model=MODEL) 
7745   
7746          # GRID inc of 7 was found to be appropriate not to find pA = 0.5. 
7747          GRID_INC = 7 
7748   
7749          # Store grid and minimisations results. 
7750          grid_results = [] 
7751          mini_results = [] 
7752          clust_results = [] 
7753   
7754          # Set the R20 parameters in the default grid search using the minimum R2eff value. 
7755          self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
7756   
7757          # Deselect insignificant spins. 
7758          self.interpreter.relax_disp.insignificance(level=1.0) 
7759   
7760          # Perform Grid Search. 
7761          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID_INC, constraints=True, verbosity=1) 
7762   
7763          # Store result. 
7764          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7765              # Store grid results. 
7766              grid_results.append([spin.r2[r20_key_600], spin.r2[r20_key_500], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
7767   
7768          ## Now do minimisation. 
7769          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
7770          set_func_tol = 1e-9 
7771          set_max_iter = 100000 
7772          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
7773   
7774          # Store result. 
7775          pA_values = [] 
7776          kex_values = [] 
7777          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7778              # Store minimisation results. 
7779              mini_results.append([spin.r2[r20_key_600], spin.r2[r20_key_500], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
7780   
7781              # Store pA values. 
7782              pA_values.append(spin.pA) 
7783   
7784              # Store kex values. 
7785              kex_values.append(spin.kex) 
7786   
7787          print("\n# Now print before and after minimisation.\n") 
7788   
7789          # Print results. 
7790          for i in range(len(grid_results)): 
7791              # Get values. 
7792              g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 
7793              m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 
7794   
7795              print("GRID r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 
7796              print("MIN  r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 
7797   
7798          ## Prepare for clustering 
7799          # Change pipe. 
7800          pipe_name_MODEL_CLUSTER = "%s_%s_Cluster"%(pipe_name, MODEL) 
7801          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL_CLUSTER) 
7802          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL_CLUSTER) 
7803   
7804          # Then select model. 
7805          self.interpreter.relax_disp.select_model(model=MODEL) 
7806   
7807          # Define cluster id. 
7808          cluster_id = 'clust' 
7809   
7810          # Loop over spins to cluster them. 
7811          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7812              self.interpreter.relax_disp.cluster(cluster_id, spin_id) 
7813   
7814          # Copy over values. 
7815          self.interpreter.relax_disp.parameter_copy(pipe_from=pipe_name_MODEL, pipe_to=pipe_name_MODEL_CLUSTER) 
7816   
7817          # Test the median values is correct 
7818          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7819              print(pA_values) 
7820              # The the median pA value returned. 
7821              self.assertEqual(median(pA_values), spin.pA) 
7822   
7823              # The the median kex value returned. 
7824              self.assertEqual(median(kex_values), spin.kex) 
7825   
7826          ## Now do minimisation. 
7827          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
7828   
7829          # Store result. 
7830          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7831              # Store clust results. 
7832              clust_results.append([spin.r2[r20_key_600], spin.r2[r20_key_500], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
7833   
7834              # Store the outcome of the clustering minimisation. 
7835              clust_pA = spin.pA 
7836              clust_kex = spin.kex 
7837   
7838          print("\n# Now testing.\n") 
7839   
7840          # Define results 
7841          test_res = {} 
7842          test_res[':10@N'] = {} 
7843          test_res[':10@N']['r2600'] = 18.429755324773360 
7844          test_res[':10@N']['r2500'] = 16.981349161968630 
7845          test_res[':10@N']['dw'] = 2.700755859433969 
7846          test_res[':10@N']['pA'] = 0.971531659288657 
7847          test_res[':10@N']['kex'] = 3831.766337047963134 
7848          test_res[':11@N'] = {} 
7849          test_res[':11@N']['r2600'] = 18.193409421115213 
7850          test_res[':11@N']['r2500'] = 17.308838135567765 
7851          test_res[':11@N']['dw'] = 2.706650302761793 
7852          test_res[':11@N']['pA'] = 0.971531659288657 
7853          test_res[':11@N']['kex'] = 3831.766337047963134 
7854   
7855          # Then make tests. 
7856          for i in range(len(grid_results)): 
7857              # Get values. 
7858              g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 
7859              m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 
7860              c_r2_600, c_r2_500, c_dw, c_pA, c_kex, c_chi2, c_spin_id, c_resi, c_resn = clust_results[i] 
7861   
7862              print("%s GRID   r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(g_spin_id, g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 
7863              print("%s MIN    r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(m_spin_id, m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 
7864              print("%s Clust  r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(m_spin_id, c_r2_600, c_r2_500, c_dw, c_pA, c_kex, c_chi2, c_spin_id, c_resi, c_resn)) 
7865   
7866              # Make tests. 
7867              self.assertEqual(clust_pA, c_pA) 
7868              self.assertEqual(clust_kex, c_kex) 
7869   
7870              # Test values. 
7871              if c_spin_id in test_res: 
7872                  self.assertAlmostEqual(c_r2_600, test_res[c_spin_id]['r2600'], 4) 
7873                  self.assertAlmostEqual(c_r2_500, test_res[c_spin_id]['r2500'], 4) 
7874                  self.assertAlmostEqual(c_dw, test_res[c_spin_id]['dw'], 3) 
7875                  self.assertAlmostEqual(c_pA, test_res[c_spin_id]['pA'], 5) 
7876                  self.assertAlmostEqual(c_kex, test_res[c_spin_id]['kex'], 1) 
7877   
7878          # Save disp graph to temp. 
7879          #self.interpreter.relax_disp.plot_disp_curves(dir="~"+sep+"test", num_points=1000, extend=500.0, force=True). 
7880   
7881   
7882 -    def test_sod1wt_t25_to_sherekhan_input(self): 
7883          """Conversion of SOD1-WT CPMG R2eff values into input files for sherekhan. 
7884   
7885          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
7886          'SOD1-WT' CPMG data to the CR72 dispersion model. 
7887   
7888          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
7889          Data is for experiment at 25 degree Celcius. 
7890          """ 
7891   
7892          # Base data setup. 
7893          pipe_name = 'base pipe' 
7894          pipe_type = 'relax_disp' 
7895          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
7896          select_spin_index = list(range(0, 2)) 
7897          self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 
7898   
7899          # Generate r20 key. 
7900          r20_key_600 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.8908617*1E6) 
7901          r20_key_500 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=499.862139*1E6) 
7902   
7903          # Cluster everything, to analyse together. 
7904          self.interpreter.relax_disp.cluster(cluster_id='all', spin_id=":1-1000") 
7905   
7906          # Write input 
7907          self.interpreter.relax_disp.sherekhan_input(force=True, spin_id=None, dir=ds.tmpdir) 
7908   
7909          # Check the r2eff set files. 
7910          print("\nChecking the R2eff input set files.") 
7911          files = [[ds.tmpdir + sep + 'cluster1', 'sherekhan_frq1.in'], [ ds.tmpdir + sep + 'cluster1', 'sherekhan_frq2.in']] 
7912   
7913          # First check file exists 
7914          for dir, file in files: 
7915              print(dir+sep+file) 
7916              self.assert_(access(dir+sep+file, F_OK)) 
7917   
7918          # Define how files should look like 
7919          data_set_600 = [ 
7920               "60.8272464287\n", 
7921               "0.06\n", 
7922               "# nu_cpmg (Hz)       R2eff (rad/s)        Error               \n", 
7923               "# G10\n", 
7924               "              33.333       26.53556078711      0.5236104771163\n", 
7925               "              66.667       25.29735243318        0.48766574122\n", 
7926               "                 100       25.09470361403      0.4820438864671\n", 
7927               "             133.333       25.15603274331      0.4837377286085\n", 
7928               "             166.667       24.27213341753      0.4599457904395\n", 
7929               "                 200       24.00364120328      0.4529773198905\n", 
7930               "             266.667       24.03511395168      0.4537880662536\n", 
7931               "                 300       23.04761040024      0.4291039120557\n", 
7932               "             333.333       22.95530300787      0.4268745963972\n", 
7933               "                 400       23.06158810662      0.4294426293624\n", 
7934               "             466.667       22.26799054092      0.4106809618644\n", 
7935               "             533.333       21.99851418823      0.4045232104735\n", 
7936               "             666.667       21.19651570955      0.3868136173831\n", 
7937               "             833.333       20.30938498379      0.3682604887899\n", 
7938               "                1000       20.28273252609       0.367719392568\n", 
7939               "# D11\n", 
7940               "              33.333       24.76520269878      0.5026475808706\n", 
7941               "              66.667        24.8773107448      0.5058752916906\n", 
7942               "                 100       24.90357815239      0.5066348551479\n", 
7943               "             133.333        23.7782506151      0.4751950583865\n", 
7944               "             166.667       23.68548762076      0.4727017128631\n", 
7945               "                 200       23.58629651618      0.4700517377679\n", 
7946               "             266.667       23.47734671187      0.4671601744044\n", 
7947               "                 300       24.08647493772      0.4835855560598\n", 
7948               "             333.333       22.98314371029      0.4542918950801\n", 
7949               "                 400       22.80339361568      0.4497107885587\n", 
7950               "             466.667       22.91634335366      0.4525833037874\n", 
7951               "             533.333       22.59774140046      0.4445334311324\n", 
7952               "             666.667        20.9177750759      0.4046955726046\n", 
7953               "             833.333       20.71792550566      0.4002363835007\n", 
7954               "                1000       19.54080006349      0.3751112751853\n", 
7955          ] 
7956   
7957          # Check data_set_600 
7958          file = open(files[0][0]+sep+files[0][1]) 
7959          lines = file.readlines() 
7960          file.close() 
7961          self.assertEqual(len(data_set_600), len(lines)) 
7962          for i in range(len(data_set_600)): 
7963              # Make the string test 
7964              self.assertEqual(data_set_600[i], lines[i]) 
7965   
7966          # Define how files should look like 
7967          data_set_500 = [ 
7968               "50.6846152368\n", 
7969               "0.04\n", 
7970               "# nu_cpmg (Hz)       R2eff (rad/s)        Error               \n", 
7971               "# G10\n", 
7972               "                  50       22.28084307393      0.2944966344183\n", 
7973               "                 100       21.93494977761      0.2910362768307\n", 
7974               "                 150       21.09850032232       0.282892238351\n", 
7975               "                 200       20.86493960397      0.2806737853646\n", 
7976               "                 250       20.75287269752      0.2796178205016\n", 
7977               "                 300       20.25597152406      0.2750013546989\n", 
7978               "                 350       19.92172163467      0.2719555756504\n", 
7979               "                 400       19.97712052922       0.272457105051\n", 
7980               "                 450       19.46807010415      0.2678972122793\n", 
7981               "                 500       19.76875460947      0.2705774849203\n", 
7982               "                 550       19.39161367402      0.2672216964327\n", 
7983               "                 600       19.03949517697      0.2641417899694\n", 
7984               "                 650       19.12218812132      0.2648605059901\n", 
7985               "                 700       19.01037461457      0.2638893584683\n", 
7986               "                 800       18.83395162904      0.2623674321143\n", 
7987               "                 900       18.47529972436      0.2593123604687\n", 
7988               "                1000        18.5252023121      0.2597343394038\n", 
7989               "# D11\n", 
7990               "                  50       22.15403890237      0.3285588379827\n", 
7991               "                 100       21.80946781746      0.3247185598713\n", 
7992               "                 150       21.77715415505       0.324361526682\n", 
7993               "                 200       21.41647464235      0.3204122024881\n", 
7994               "                 250       21.17099940822      0.3177616325958\n", 
7995               "                 300       21.03740030577      0.3163316496664\n", 
7996               "                 350       20.95393648281      0.3154427665172\n", 
7997               "                 400       20.93311399332       0.315221543436\n", 
7998               "                 450       20.18219905222      0.3073848655291\n", 
7999               "                 500       19.93599065085      0.3048744697057\n", 
8000               "                 550       19.68475725452      0.3023424499113\n", 
8001               "                 600       19.33575433934      0.2988741928798\n", 
8002               "                 650       19.53915692194      0.3008886196853\n", 
8003               "                 700        19.2018754351      0.2975587767134\n", 
8004               "                 800       18.82360965368      0.2938866923878\n", 
8005               "                 900       18.71861761238      0.2928790380131\n", 
8006               "                1000       17.95878049287      0.2857341721151\n", 
8007          ] 
8008   
8009          # Check data_set_500 
8010          file = open(files[1][0]+sep+files[1][1]) 
8011          lines = file.readlines() 
8012          file.close() 
8013          self.assertEqual(len(data_set_500), len(lines)) 
8014          for i in range(len(data_set_500)): 
8015              # Make the string test 
8016              self.assertEqual(data_set_500[i], lines[i]) 
8017   
8018          # Test local dir tests. This will be turned off in system test. 
8019          turn_on_local_dir_test = False 
8020   
8021          if turn_on_local_dir_test: 
8022              ## Now check to local folder with None argument. 
8023              # Write input 
8024              self.interpreter.relax_disp.sherekhan_input(force=True, spin_id=None) 
8025   
8026              # Check the r2eff set files. 
8027              print("\nChecking the R2eff input set files.") 
8028              files = [[path.join(getcwd(), 'cluster1'), 'sherekhan_frq1.in'], [path.join(getcwd(), 'cluster1'), 'sherekhan_frq2.in']] 
8029   
8030              # First check file exists 
8031              for dir, file in files: 
8032                  print(dir+sep+file) 
8033                  self.assert_(access(dir+sep+file, F_OK)) 
8034   
8035              ## Now check to local folder with dir argument. 
8036              # Write input 
8037              set_dir = "Test_ShereKhan" 
8038              self.interpreter.relax_disp.sherekhan_input(force=True, spin_id=None, dir=set_dir) 
8039   
8040              # Check the r2eff set files. 
8041              print("\nChecking the R2eff input set files.") 
8042              files = [[path.join(getcwd(), set_dir, 'cluster1'), 'sherekhan_frq1.in'], [path.join(getcwd(), set_dir, 'cluster1'), 'sherekhan_frq2.in']] 
8043   
8044              # First check file exists 
8045              for dir, file in files: 
8046                  print(dir+sep+file) 
8047                  self.assert_(access(dir+sep+file, F_OK)) 
8048   
8049   
8050 -    def test_sprangers_data_to_mmq_cr72(self, model=None): 
8051          """Test the 'MMQ CR72' model fitting against Remco Sprangers' ClpP data. 
8052   
8053          This uses the data from Remco Sprangers' paper at http://dx.doi.org/10.1073/pnas.0507370102.  This is MMQ CPMG data with a fixed relaxation time period. 
8054          """ 
8055   
8056          # Reset. 
8057          self.interpreter.reset() 
8058   
8059          # Create the data pipe and load the base data. 
8060          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Sprangers_ClpP' 
8061          self.interpreter.state.load(data_path+sep+'r2eff_values') 
8062   
8063          # The model data pipe. 
8064          model = 'MMQ CR72' 
8065          pipe_name = "%s - relax_disp" % model 
8066          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
8067          self.interpreter.pipe.switch(pipe_name=pipe_name) 
8068   
8069          # Set the model. 
8070          self.interpreter.relax_disp.select_model(model=model) 
8071   
8072          # Cluster everything. 
8073          self.interpreter.relax_disp.cluster(cluster_id='all', spin_id=":135-137") 
8074   
8075          # Copy the data. 
8076          self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff') 
8077   
8078          # Alias the spins. 
8079          spin135S = cdp.mol[0].res[0].spin[0] 
8080          spin135F = cdp.mol[0].res[0].spin[1] 
8081          spin137S = cdp.mol[0].res[1].spin[0] 
8082          spin137F = cdp.mol[0].res[1].spin[1] 
8083   
8084          # The R20 keys. 
8085          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=600e6) 
8086          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
8087   
8088          # Set the cluster specific parameters (only for the first spin). 
8089          spin135S.pA = 0.836591763632 
8090          spin135S.kex = 241.806525261 
8091   
8092          # Set the initial parameter values. 
8093          spin135S.r2 = {r20_key1: 28.2493431552, r20_key2: 31.7517334715} 
8094          spin135S.dw = 0.583003118785 
8095          spin135S.dwH = 0.0361441944301 
8096   
8097          spin135F.r2 = {r20_key1: 42.7201839991, r20_key2: 57.3178617389} 
8098          spin135F.dw = 0.805849745104 
8099          spin135F.dwH = 0.0215791945715 
8100   
8101          spin137S.r2 = {r20_key1: 26.0134115256, r20_key2: 30.575806934} 
8102          spin137S.dw = 0.688107568372 
8103          spin137S.dwH = 0.0344463604043 
8104   
8105          spin137F.r2 = {r20_key1: 46.6969397337, r20_key2: 58.602384101} 
8106          spin137F.dw = 0.94978299907 
8107          spin137F.dwH = 1.4818877939e-07 
8108   
8109          # Low precision optimisation. 
8110          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-10, max_iter=1000) 
8111   
8112          # Printout. 
8113          print("\n\nOptimised parameters:\n") 
8114          print("%-20s %-20s %-20s %-20s %-20s" % ("Parameter", "Value (:135@S)", "Value (:135@F)", "Value (:137@S)", "Value (:137@F)")) 
8115          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin135S.r2[r20_key1], spin135F.r2[r20_key1], spin137S.r2[r20_key1], spin137F.r2[r20_key1])) 
8116          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin135S.r2[r20_key2], spin135F.r2[r20_key2], spin137S.r2[r20_key2], spin137F.r2[r20_key2])) 
8117          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("pA", spin135S.pA, spin135F.pA, spin137S.pA, spin137F.pA)) 
8118          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dw", spin135S.dw, spin135F.dw, spin137S.dw, spin137F.dw)) 
8119          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dwH", spin135S.dwH, spin135F.dwH, spin137S.dwH, spin137F.dwH)) 
8120          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("kex", spin135S.kex, spin135F.kex, spin137S.kex, spin137F.kex)) 
8121          print("%-20s %20.15g %20.15g %20.15g %20.15g\n" % ("chi2", spin135S.chi2, spin135F.chi2, spin137S.chi2, spin137F.chi2)) 
8122          print("\n        # Set the cluster specific parameters (only for the first spin).") 
8123          print("        spin135S.pA = %s" % spin135S.pA) 
8124          print("        spin135S.kex = %s" % spin135S.kex) 
8125          print("\n        # Set the initial parameter values.") 
8126          print("        spin135S.r2 = {r20_key1: %s, r20_key2: %s}" % (spin135S.r2[r20_key1], spin135S.r2[r20_key2])) 
8127          print("        spin135S.dw = %s" % spin135S.dw) 
8128          print("        spin135S.dwH = %s" % spin135S.dwH) 
8129          print("\n        spin135F.r2 = {r20_key1: %s, r20_key2: %s}" % (spin135F.r2[r20_key1], spin135F.r2[r20_key2])) 
8130          print("        spin135F.dw = %s" % spin135F.dw) 
8131          print("        spin135F.dwH = %s" % spin135F.dwH) 
8132          print("\n        spin137S.r2 = {r20_key1: %s, r20_key2: %s}" % (spin137S.r2[r20_key1], spin137S.r2[r20_key2])) 
8133          print("        spin137S.dw = %s" % spin137S.dw) 
8134          print("        spin137S.dwH = %s" % spin137S.dwH) 
8135          print("\n        spin137F.r2 = {r20_key1: %s, r20_key2: %s}" % (spin137F.r2[r20_key1], spin137F.r2[r20_key2])) 
8136          print("        spin137F.dw = %s" % spin137F.dw) 
8137          print("        spin137F.dwH = %s" % spin137F.dwH) 
8138   
8139          # Checks for residue :135S. 
8140          self.assertAlmostEqual(spin135S.r2[r20_key1], 28.2493445347425, 4) 
8141          self.assertAlmostEqual(spin135S.r2[r20_key2], 31.7517352342937, 4) 
8142          self.assertAlmostEqual(spin135S.pA, 0.836591714049569, 4) 
8143          self.assertAlmostEqual(spin135S.dw, 0.583003004605869, 4) 
8144          self.assertAlmostEqual(spin135S.dwH, 0.0361441894065963, 4) 
8145          self.assertAlmostEqual(spin135S.kex/100, 241.806464344233/100, 4) 
8146          self.assertAlmostEqual(spin135S.chi2, 12.4224060116473, 4) 
8147   
8148          # Checks for residue :135F. 
8149          self.assertAlmostEqual(spin135F.r2[r20_key1], 42.7201844426839, 4) 
8150          self.assertAlmostEqual(spin135F.r2[r20_key2], 57.3178718548898, 4) 
8151          self.assertAlmostEqual(spin135F.pA, 0.836591714049569, 4) 
8152          self.assertAlmostEqual(spin135F.dw, 0.805849748711916, 4) 
8153          self.assertAlmostEqual(spin135F.dwH, 0.0215791669142752, 4) 
8154          self.assertAlmostEqual(spin135F.kex/100, 241.806464344233/100, 4) 
8155          self.assertAlmostEqual(spin135F.chi2, 12.4224060116473, 4) 
8156   
8157          # Checks for residue :137S. 
8158          self.assertAlmostEqual(spin137S.r2[r20_key1], 26.013412509919, 4) 
8159          self.assertAlmostEqual(spin137S.r2[r20_key2], 30.5758092335097, 4) 
8160          self.assertAlmostEqual(spin137S.pA, 0.836591714049569, 4) 
8161          self.assertAlmostEqual(spin137S.dw, 0.688107406812537, 4) 
8162          self.assertAlmostEqual(spin137S.dwH, 0.034446357344577, 4) 
8163          self.assertAlmostEqual(spin137S.kex/100, 241.806464344233/100, 4) 
8164          self.assertAlmostEqual(spin137S.chi2, 12.4224060116473, 4) 
8165   
8166          # Checks for residue :137F. 
8167          self.assertAlmostEqual(spin137F.r2[r20_key1], 46.696935090697, 4) 
8168          self.assertAlmostEqual(spin137F.r2[r20_key2], 58.6023842513446, 4) 
8169          self.assertAlmostEqual(spin137F.pA, 0.836591714049569, 4) 
8170          self.assertAlmostEqual(spin137F.dw, 0.94978325541294, 4) 
8171          self.assertAlmostEqual(spin137F.dwH, 1.5189362257653e-07, 4) 
8172          self.assertAlmostEqual(spin137F.kex/100, 241.806464344233/100, 4) 
8173          self.assertAlmostEqual(spin137F.chi2, 12.4224060116473, 4) 
8174   
8175   
8176 -    def test_sprangers_data_to_ns_mmq_2site(self, model=None): 
8177          """Test the 'NS MMQ 2-site' model fitting against Remco Sprangers' ClpP data. 
8178   
8179          This uses the data from Remco Sprangers' paper at http://dx.doi.org/10.1073/pnas.0507370102.  This is MQ CPMG data with a fixed relaxation time period. 
8180          """ 
8181   
8182          # Reset. 
8183          self.interpreter.reset() 
8184   
8185          # Create the data pipe and load the base data. 
8186          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Sprangers_ClpP' 
8187          self.interpreter.state.load(data_path+sep+'r2eff_values') 
8188   
8189          # The model data pipe. 
8190          model = 'NS MMQ 2-site' 
8191          pipe_name = "%s - relax_disp" % model 
8192          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
8193          self.interpreter.pipe.switch(pipe_name=pipe_name) 
8194   
8195          # Set the model. 
8196          self.interpreter.relax_disp.select_model(model=model) 
8197   
8198          # Cluster everything. 
8199          self.interpreter.relax_disp.cluster(cluster_id='all', spin_id=":135-137") 
8200   
8201          # Copy the data. 
8202          self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff') 
8203   
8204          # Alias the spins. 
8205          spin135S = cdp.mol[0].res[0].spin[0] 
8206          spin135F = cdp.mol[0].res[0].spin[1] 
8207          spin137S = cdp.mol[0].res[1].spin[0] 
8208          spin137F = cdp.mol[0].res[1].spin[1] 
8209   
8210          # The R20 keys. 
8211          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
8212          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
8213   
8214          # Set the cluster specific parameters (only for the first spin). 
8215          spin135S.pA = 0.847378444499757 
8216          spin135S.kex = 264.055604934724329 
8217   
8218          # Set the initial parameter values. 
8219          spin135S.r2 = {r20_key1: 30.315119723745390, r20_key2: 37.411874745645299} 
8220          spin135S.dw = 0.585574008745351 
8221          spin135S.dwH = 0.000000000000002 
8222   
8223          spin135F.r2 = {r20_key1: 41.440843383778287, r20_key2: 56.989726795397893} 
8224          spin135F.dw = 0.856699277665748 
8225          spin135F.dwH = 0.000000000582587 
8226   
8227          spin137S.r2 = {r20_key1: 23.051695938570266, r20_key2: 28.352806483953824} 
8228          spin137S.dw = 0.772904450844973 
8229          spin137S.dwH = 0.183351478512970 
8230   
8231          spin137F.r2 = {r20_key1: 44.702032074210429, r20_key2: 56.453146052685319} 
8232          spin137F.dw = 0.984568590342831 
8233          spin137F.dwH = 0.000000001993458 
8234   
8235          # Low precision optimisation. 
8236          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-5, grad_tol=None, max_iter=100, constraints=True, scaling=True, verbosity=1) 
8237   
8238          # Printout. 
8239          print("\n\nOptimised parameters:\n") 
8240          print("%-20s %-20s %-20s %-20s %-20s" % ("Parameter", "Value (:135@S)", "Value (:135@F)", "Value (:137@S)", "Value (:137@F)")) 
8241          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin135S.r2[r20_key1], spin135F.r2[r20_key1], spin137S.r2[r20_key1], spin137F.r2[r20_key1])) 
8242          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin135S.r2[r20_key2], spin135F.r2[r20_key2], spin137S.r2[r20_key2], spin137F.r2[r20_key2])) 
8243          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("pA", spin135S.pA, spin135F.pA, spin137S.pA, spin137F.pA)) 
8244          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dw", spin135S.dw, spin135F.dw, spin137S.dw, spin137F.dw)) 
8245          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dwH", spin135S.dwH, spin135F.dwH, spin137S.dwH, spin137F.dwH)) 
8246          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("kex", spin135S.kex, spin135F.kex, spin137S.kex, spin137F.kex)) 
8247          print("%-20s %20.15g %20.15g %20.15g %20.15g\n" % ("chi2", spin135S.chi2, spin135F.chi2, spin137S.chi2, spin137F.chi2)) 
8248   
8249          # FIXME: Remove this temporary return and properly check the results. 
8250          return 
8251   
8252          # Checks for residue :135S. 
8253          self.assertAlmostEqual(spin135S.r2[r20_key1], 30.3151197237454, 4) 
8254          self.assertAlmostEqual(spin135S.r2[r20_key2], 37.4118747456453, 4) 
8255          self.assertAlmostEqual(spin135S.pA, 0.847378444499757, 4) 
8256          self.assertAlmostEqual(spin135S.dw, 0.585574008745351, 4) 
8257          self.assertAlmostEqual(spin135S.dwH, 2e-15, 4) 
8258          self.assertAlmostEqual(spin135S.kex, 264.055604934724, 4) 
8259          self.assertAlmostEqual(spin135S.chi2, 13.859423588071, 1) 
8260   
8261          # Checks for residue :135F. 
8262          self.assertAlmostEqual(spin135F.r2[r20_key1], 41.4408433837783, 4) 
8263          self.assertAlmostEqual(spin135F.r2[r20_key2], 56.9897267953979, 4) 
8264          self.assertAlmostEqual(spin135F.pA, 0.847378444499757, 4) 
8265          self.assertAlmostEqual(spin135F.dw, 0.856699277665748, 4) 
8266          self.assertAlmostEqual(spin135F.dwH, 5.82587e-10, 4) 
8267          self.assertAlmostEqual(spin135F.kex, 264.055604934724, 4) 
8268          self.assertAlmostEqual(spin135F.chi2, 13.859423588071, 1) 
8269   
8270          # Checks for residue :137S. 
8271          self.assertAlmostEqual(spin137S.r2[r20_key1], 23.0516959385703, 4) 
8272          self.assertAlmostEqual(spin137S.r2[r20_key2], 28.3528064839538, 4) 
8273          self.assertAlmostEqual(spin137S.pA, 0.847378444499757, 4) 
8274          self.assertAlmostEqual(spin137S.dw, 0.772904450844973, 4) 
8275          self.assertAlmostEqual(spin137S.dwH, 0.18335147851297, 4) 
8276          self.assertAlmostEqual(spin137S.kex, 264.055604934724, 4) 
8277          self.assertAlmostEqual(spin137S.chi2, 13.859423588071, 1) 
8278   
8279          # Checks for residue :137F. 
8280          self.assertAlmostEqual(spin137F.r2[r20_key1], 44.7020320742104, 4) 
8281          self.assertAlmostEqual(spin137F.r2[r20_key2], 56.4531460526853, 4) 
8282          self.assertAlmostEqual(spin137F.pA, 0.847378444499757, 4) 
8283          self.assertAlmostEqual(spin137F.dw, 0.984568590342831, 4) 
8284          self.assertAlmostEqual(spin137F.dwH, 2.0931309e-09, 4) 
8285          self.assertAlmostEqual(spin137F.kex, 264.055604934724, 4) 
8286          self.assertAlmostEqual(spin137F.chi2, 13.859423588071, 1) 
8287   
8288   
8289 -    def test_tp02_data_to_ns_r1rho_2site(self, model=None): 
8290          """Test the relaxation dispersion 'NS R1rho 2-site' model fitting against the 'TP02' test data.""" 
8291   
8292          # Setup the data. 
8293          self.setup_tp02_data_to_ns_r1rho_2site() 
8294   
8295          # Alias the spins. 
8296          spin1 = cdp.mol[0].res[0].spin[0] 
8297          spin2 = cdp.mol[0].res[1].spin[0] 
8298   
8299          # The R20 keys. 
8300          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8301          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8302   
8303          # Checks for residue :1. 
8304          self.assertAlmostEqual(spin1.r2[r20_key1], 8.50207717367548, 4) 
8305          self.assertAlmostEqual(spin1.r2[r20_key2], 13.4680429589972, 4) 
8306          self.assertAlmostEqual(spin1.pA, 0.864523128842393, 4) 
8307          self.assertAlmostEqual(spin1.dw, 8.85204828994151, 4) 
8308          self.assertAlmostEqual(spin1.kex/1000, 1199.56359549637/1000, 4) 
8309          self.assertAlmostEqual(spin1.chi2, 2.99182130153514, 4) 
8310   
8311          # Checks for residue :2. 
8312          self.assertAlmostEqual(spin2.r2[r20_key1], 10.2099357790203, 4) 
8313          self.assertAlmostEqual(spin2.r2[r20_key2], 16.2137648697873, 4) 
8314          self.assertAlmostEqual(spin2.pA, 0.836488681031685, 4) 
8315          self.assertAlmostEqual(spin2.dw, 9.5505714779503, 4) 
8316          self.assertAlmostEqual(spin2.kex/1000, 1454.45726998929/1000, 4) 
8317          self.assertAlmostEqual(spin2.chi2, 0.000402231563481261, 4) 
8318   
8319   
8320 -    def test_tp02_data_to_ns_r1rho_2site_cluster(self, model=None): 
8321          """Test the relaxation dispersion 'NS R1rho 2-site' model fitting against the 'TP02' test data, when performing clustering.""" 
8322   
8323          # Setup the data. 
8324          self.setup_tp02_data_to_ns_r1rho_2site(clustering=True) 
8325   
8326          # Alias the spins. 
8327          spin1 = cdp.mol[0].res[0].spin[0] 
8328          spin2 = cdp.mol[0].res[1].spin[0] 
8329   
8330          # The R20 keys. 
8331          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8332          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8333   
8334          # Checks for residue :1. 
8335          self.assertAlmostEqual(spin1.r2[r20_key1], 8.48607207881462, 4) 
8336          self.assertAlmostEqual(spin1.r2[r20_key2], 13.4527609061722, 4) 
8337          self.assertAlmostEqual(spin1.pA, 0.863093838784425, 4) 
8338          self.assertAlmostEqual(spin1.dw, 8.86218096536618, 4) 
8339          self.assertAlmostEqual(spin1.kex/1000, 1186.22749648299/1000, 4) 
8340          self.assertAlmostEqual(spin1.chi2, 3.09500996065247, 4) 
8341   
8342          # Checks for residue :2. 
8343          self.assertAlmostEqual(spin2.r2[r20_key1], 10.4577906018883, 4) 
8344          self.assertAlmostEqual(spin2.r2[r20_key2], 16.4455550953792, 4) 
8345          self.assertAlmostEqual(spin2.pA, 0.863093838784425, 4) 
8346          self.assertAlmostEqual(spin2.dw, 11.5841168862587, 4) 
8347          self.assertAlmostEqual(spin2.kex/1000, 1186.22749648299/1000, 4) 
8348          self.assertAlmostEqual(spin2.chi2, 3.09500996065247, 4) 
8349   
8350   
8351 -    def test_tp02_data_to_mp05(self): 
8352          """Test the dispersion 'MP05' model fitting against the 'TP02' test data.""" 
8353   
8354          # Fixed time variable and the models. 
8355          ds.fixed = True 
8356          ds.models = ['R2eff', 'MP05'] 
8357   
8358          # Execute the script. 
8359          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_off_res_tp02.py') 
8360   
8361          # Switch back to the data pipe for the optimisation. 
8362          self.interpreter.pipe.switch('MP05 - relax_disp') 
8363   
8364          # The equivalent MP05 parameters. 
8365          r1rho_prime = [[10.0058086343329, 15.005806870124], [12.0766320470785, 18.0767503536277]] 
8366          pA = [0.775055484521586, 0.500000000036595] 
8367          kex = [1235.20361276079, 2378.31403454691] 
8368          delta_omega = [7.08194146569694, 5.4083562844306] 
8369          chi2 = [0.0370400968727768, 0.182141732163934] 
8370   
8371          # Alias the spins. 
8372          spin1 = cdp.mol[0].res[0].spin[0] 
8373          spin2 = cdp.mol[0].res[1].spin[0] 
8374   
8375          # The R20 keys. 
8376          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8377          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8378   
8379          # Printout. 
8380          print("\n\nOptimised parameters:\n") 
8381          print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 
8382          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 
8383          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 
8384          print("%-20s %20.15g %20.15g" % ("pA", spin1.pA, spin2.pA)) 
8385          print("%-20s %20.15g %20.15g" % ("dw", spin1.dw, spin2.dw)) 
8386          print("%-20s %20.15g %20.15g" % ("kex", spin1.kex, spin2.kex)) 
8387          print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 
8388   
8389          # Check each spin. 
8390          spin_index = 0 
8391          for spin, spin_id in spin_loop(return_id=True): 
8392              # Printout. 
8393              print("\nSpin %s." % spin_id) 
8394   
8395              # Check the fitted parameters. 
8396              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index][0]/10, 4) 
8397              self.assertAlmostEqual(spin.r2[r20_key2]/10, r1rho_prime[spin_index][1]/10, 4) 
8398              self.assertAlmostEqual(spin.pA, pA[spin_index], 3) 
8399              self.assertAlmostEqual(spin.dw, delta_omega[spin_index], 3) 
8400              self.assertAlmostEqual(spin.kex/1000.0, kex[spin_index]/1000.0, 3) 
8401              self.assertAlmostEqual(spin.chi2, chi2[spin_index], 3) 
8402   
8403              # Increment the spin index. 
8404              spin_index += 1 
8405   
8406   
8407 -    def test_tp02_data_to_tap03(self): 
8408          """Test the dispersion 'TAP03' model fitting against the 'TP02' test data.""" 
8409   
8410          # Fixed time variable and the models. 
8411          ds.fixed = True 
8412          ds.models = ['R2eff', 'TAP03'] 
8413   
8414          # Execute the script. 
8415          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_off_res_tp02.py') 
8416   
8417          # Switch back to the data pipe for the optimisation. 
8418          self.interpreter.pipe.switch('TAP03 - relax_disp') 
8419   
8420          # The equivalent TAP03 parameters. 
8421          r1rho_prime = [[10.0058156589442, 15.005818505006], [12.0766046472748, 18.076648462452]] 
8422          pA = [0.775042569092891, 0.500000000229685] 
8423          kex = [1235.20852748765, 2379.47085580169] 
8424          delta_omega = [7.08176806468445, 5.40708372863538] 
8425          chi2 = [0.0371366837083293, 0.182212857256044] 
8426   
8427          # Alias the spins. 
8428          spin1 = cdp.mol[0].res[0].spin[0] 
8429          spin2 = cdp.mol[0].res[1].spin[0] 
8430   
8431          # The R20 keys. 
8432          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8433          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8434   
8435          # Printout. 
8436          print("\n\nOptimised parameters:\n") 
8437          print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 
8438          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 
8439          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 
8440          print("%-20s %20.15g %20.15g" % ("pA", spin1.pA, spin2.pA)) 
8441          print("%-20s %20.15g %20.15g" % ("dw", spin1.dw, spin2.dw)) 
8442          print("%-20s %20.15g %20.15g" % ("kex", spin1.kex, spin2.kex)) 
8443          print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 
8444   
8445          # Switch to the 'MP05' model data pipe, then check for each spin. 
8446          self.interpreter.pipe.switch('TAP03 - relax_disp') 
8447          spin_index = 0 
8448          for spin, spin_id in spin_loop(return_id=True): 
8449              # Printout. 
8450              print("\nSpin %s." % spin_id) 
8451   
8452              # Check the fitted parameters. 
8453              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index][0]/10, 4) 
8454              self.assertAlmostEqual(spin.r2[r20_key2]/10, r1rho_prime[spin_index][1]/10, 4) 
8455              self.assertAlmostEqual(spin.pA, pA[spin_index], 3) 
8456              self.assertAlmostEqual(spin.dw, delta_omega[spin_index], 3) 
8457              self.assertAlmostEqual(spin.kex/1000.0, kex[spin_index]/1000.0, 3) 
8458              self.assertAlmostEqual(spin.chi2, chi2[spin_index], 3) 
8459   
8460              # Increment the spin index. 
8461              spin_index += 1 
8462   
8463   
8464 -    def test_tp02_data_to_tp02(self): 
8465          """Test the relaxation dispersion 'TP02' model curve fitting to fixed time synthetic data.""" 
8466   
8467          # Fixed time variable. 
8468          ds.fixed = True 
8469   
8470          # Execute the script. 
8471          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_off_res_tp02.py') 
8472   
8473          # The original parameters. 
8474          r1rho_prime = [[10.0, 15.0], [12.0, 18.0]] 
8475          pA = 0.7654321 
8476          kex = 1234.56789 
8477          delta_omega = [7.0, 9.0] 
8478   
8479          # The R20 keys. 
8480          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8481          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8482   
8483          # Switch to the 'TP02' model data pipe, then check for each spin. 
8484          self.interpreter.pipe.switch('TP02 - relax_disp') 
8485          spin_index = 0 
8486          for spin, spin_id in spin_loop(return_id=True): 
8487              # Printout. 
8488              print("\nSpin %s." % spin_id) 
8489   
8490              # Check the fitted parameters. 
8491              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index][0]/10, 4) 
8492              self.assertAlmostEqual(spin.r2[r20_key2]/10, r1rho_prime[spin_index][1]/10, 4) 
8493              self.assertAlmostEqual(spin.dw, delta_omega[spin_index], 3) 
8494              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 3) 
8495   
8496              # Increment the spin index. 
8497              spin_index += 1 
8498   
8499   
8500 -    def test_value_write_calc_rotating_frame_params_int(self): 
8501          """System test of the value.write function to write intensities for an R1rho setup. 
8502          This system test is to make sure, that modifying the API for special parameters theta and w_eff does not alter the functionality value.write. 
8503   
8504          This uses the data of the saved state attached to U{bug #21344<https://gna.org/bugs/?21344>}. 
8505          """ 
8506   
8507          # Load the state. 
8508          statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 
8509          self.interpreter.state.load(statefile, force=True) 
8510   
8511          # Set filepaths. 
8512          int_filepath = ds.tmpdir+sep+'int.out' 
8513   
8514          # Write out the intensity parameter file. 
8515          # The writing out of intensity file is to make sure the API function retains its function after modification for special parameters. 
8516          self.interpreter.value.write(param='peak_intensity', file='int.out', dir=ds.tmpdir, scaling=1.0, force=True) 
8517   
8518          # Test the file exists. 
8519          self.assert_(access(int_filepath, F_OK)) 
8520   
8521          # Open the files for testing. 
8522          int_file = open(int_filepath, 'r') 
8523   
8524          # Loop over the intensity file to test values. 
8525          for line in int_file: 
8526              # Skip lines starting with #. 
8527              if line[0] == "#": 
8528                  continue 
8529   
8530              # Split the line 
8531              linesplit = line.split() 
8532   
8533              # Assume values 
8534              if linesplit[0] == "None" and linesplit[1] == "5" and linesplit[2] == "I": 
8535                  self.assertEqual(linesplit[5], "115571.4") 
8536              elif linesplit[0] == "None" and linesplit[1] == "6" and linesplit[2] == "S": 
8537                  self.assertEqual(linesplit[5], "68377.52") 
8538              elif linesplit[0] == "None" and linesplit[1] == "8" and linesplit[2] == "S": 
8539                  self.assertEqual(linesplit[5], "9141.689") 
8540              elif linesplit[0] == "None" and linesplit[1] == "9" and linesplit[2] == "A": 
8541                  self.assertEqual(linesplit[5], "29123.77") 
8542              elif linesplit[0] == "None" and linesplit[1] == "10" and linesplit[2] == "L": 
8543                  self.assertEqual(linesplit[5], "58914.94") 
8544   
8545          # Close files 
8546          int_file.close() 
8547   
8548   
8549 -    def test_value_write_calc_rotating_frame_params_theta(self): 
8550          """System test of the value.write function to write return values of theta from calc_rotating_frame_params() function for an R1rho setup. 
8551   
8552          This uses the data of the saved state attached to U{bug #21344<https://gna.org/bugs/?21344>}. 
8553          """ 
8554   
8555          # Load the state. 
8556          statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 
8557          self.interpreter.state.load(statefile, force=True) 
8558   
8559          # Set filepaths. 
8560          theta_filepath = ds.tmpdir+sep+'theta.out' 
8561   
8562          # Write out the theta parameter file. 
8563          self.interpreter.value.write(param='theta', file='theta.out', dir=ds.tmpdir, scaling=1.0, force=True) 
8564   
8565          # Test the file exists. 
8566          self.assert_(access(theta_filepath, F_OK)) 
8567   
8568          # Open the files for testing. 
8569          theta_file = open(theta_filepath, 'r') 
8570   
8571          # Loop over the theta file to test values. 
8572          for line in theta_file: 
8573              # Skip lines starting with #. 
8574              if line[0] == "#": 
8575                  continue 
8576              # Print lines, not including newline character. 
8577              print(line[:-1]) 
8578   
8579              # Split the line 
8580              linesplit = line.split() 
8581   
8582              # Assume values 
8583              if linesplit[0] == "None" and linesplit[1] == "5" and linesplit[2] == "I": 
8584                  self.assertNotEqual(linesplit[5], "None") 
8585              elif linesplit[0] == "None" and linesplit[1] == "6" and linesplit[2] == "S": 
8586                  self.assertNotEqual(linesplit[5], "None") 
8587              elif linesplit[0] == "None" and linesplit[1] == "8" and linesplit[2] == "S": 
8588                  self.assertNotEqual(linesplit[5], "None") 
8589              elif linesplit[0] == "None" and linesplit[1] == "9" and linesplit[2] == "A": 
8590                  self.assertNotEqual(linesplit[5], "None") 
8591              elif linesplit[0] == "None" and linesplit[1] == "10" and linesplit[2] == "L": 
8592                  self.assertNotEqual(linesplit[5], "None") 
8593   
8594          # Close files 
8595          theta_file.close() 
8596   
8597   
8598 -    def test_value_write_calc_rotating_frame_params_w_eff(self): 
8599          """System test of the value.write function to write return values of w_eff from calc_rotating_frame_params() function for an R1rho setup. 
8600   
8601          This uses the data of the saved state attached to U{bug #21344<https://gna.org/bugs/?21344>}. 
8602          """ 
8603   
8604          # Load the state. 
8605          statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 
8606          self.interpreter.state.load(statefile, force=True) 
8607   
8608          # Set filepaths. 
8609          w_eff_filepath = ds.tmpdir+sep+'w_eff.out' 
8610   
8611          # Write out the w_eff parameter file. 
8612          self.interpreter.value.write(param='w_eff', file='w_eff.out', dir=ds.tmpdir, scaling=1.0, force=True) 
8613   
8614          # Test the file exists. 
8615          self.assert_(access(w_eff_filepath, F_OK)) 
8616   
8617          # Open the files for testing. 
8618          w_eff_file = open(w_eff_filepath, 'r') 
8619   
8620          # Loop over the w_eff file to test values. 
8621          for line in w_eff_file: 
8622              # Skip lines starting with #. 
8623              if line[0] == "#": 
8624                  continue 
8625              # Print lines, not including newline character. 
8626              print(line[:-1]) 
8627   
8628              # Split the line 
8629              linesplit = line.split() 
8630   
8631              # Assume values 
8632              if linesplit[0] == "None" and linesplit[1] == "5" and linesplit[2] == "I": 
8633                  self.assertNotEqual(linesplit[5], "None") 
8634              elif linesplit[0] == "None" and linesplit[1] == "6" and linesplit[2] == "S": 
8635                  self.assertNotEqual(linesplit[5], "None") 
8636              elif linesplit[0] == "None" and linesplit[1] == "8" and linesplit[2] == "S": 
8637                  self.assertNotEqual(linesplit[5], "None") 
8638              elif linesplit[0] == "None" and linesplit[1] == "9" and linesplit[2] == "A": 
8639                  self.assertNotEqual(linesplit[5], "None") 
8640              elif linesplit[0] == "None" and linesplit[1] == "10" and linesplit[2] == "L": 
8641                  self.assertNotEqual(linesplit[5], "None") 
8642   
8643          # Close files 
8644          w_eff_file.close() 
8645   
8646   
8647 -    def test_value_write_calc_rotating_frame_params_auto_analysis(self): 
8648          """System test of the auto_analysis value.write function to write theta and w_eff values for an R1rho setup. 
8649   
8650          This uses the data of the saved state attached to U{bug #21344<https://gna.org/bugs/?21344>}. 
8651          """ 
8652   
8653          # Load the state. 
8654          statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344.bz2' 
8655          self.interpreter.state.load(statefile, force=True) 
8656   
8657          # Set pipe name, bundle and type. 
8658          pipe_name = 'base pipe' 
8659          pipe_bundle = 'relax_disp' 
8660          pipe_type = 'relax_disp' 
8661   
8662          # The path to the data files. 
8663          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' 
8664   
8665          # Deselect all spins 
8666          self.interpreter.deselect.all() 
8667   
8668          # Specify spins to be selected. 
8669          select_spin_ids = [ 
8670          ":13@N", 
8671          ":15@N", 
8672          ":16@N", 
8673          ":25@N", 
8674          ":26@N", 
8675          ":28@N", 
8676          ":39@N", 
8677          ":40@N", 
8678          ":41@N", 
8679          ":43@N", 
8680          ":44@N", 
8681          ":45@N", 
8682          ":49@N", 
8683          ":52@N", 
8684          ":53@N"] 
8685   
8686          # Reverse the selection for the spins. 
8687          for curspin in select_spin_ids: 
8688              print("Selecting spin %s"%curspin) 
8689              self.interpreter.deselect.reverse(spin_id=curspin) 
8690   
8691          # Read the R1 data 
8692          self.interpreter.relax_data.read(ri_id='R1', ri_type='R1', frq=cdp.spectrometer_frq_list[0], file='R1_fitted_values.txt', dir=data_path, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5, data_col=6, error_col=7) 
8693   
8694          # The dispersion models. 
8695          MODELS = ['R2eff'] 
8696   
8697          # The grid search size (the number of increments per dimension). 
8698          GRID_INC = 4 
8699   
8700          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
8701          MC_NUM = 3 
8702   
8703          # Model selection technique. 
8704          MODSEL = 'AIC' 
8705   
8706          # Execute the auto-analysis (fast). 
8707          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
8708          OPT_FUNC_TOL = 1e-1 
8709          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
8710          OPT_MAX_ITERATIONS = 1000 
8711          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
8712   
8713          # Run the analysis. 
8714          relax_disp.Relax_disp(pipe_name=pipe_name, pipe_bundle=pipe_bundle, results_dir=ds.tmpdir, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL) 
8715   
8716          ## Check for file creation 
8717          # Set filepaths. 
8718          theta_filepath = ds.tmpdir+sep+MODELS[0]+sep+'theta.out' 
8719          w_eff_filepath = ds.tmpdir+sep+MODELS[0]+sep+'w_eff.out' 
8720   
8721          # Test the files exists. 
8722          self.assert_(access(theta_filepath, F_OK)) 
8723          self.assert_(access(w_eff_filepath, F_OK)) 
8724   
8725          # Open the files for testing. 
8726          theta_file = open(theta_filepath, 'r') 
8727          theta_result = [ 
8728              "# Parameter description:  Rotating frame tilt angle : ( theta = arctan(w_1 / Omega) ) (rad).\n", 
8729              "#\n", 
8730              "# mol_name    res_num    res_name    spin_num    spin_name    r1rho_799.77739910_118.078_1341.110    sd(r1rho_799.77739910_118.078_1341.110)    r1rho_799.77739910_118.078_1648.500    sd(r1rho_799.77739910_118.078_1648.500)    r1rho_799.77739910_118.078_431.000    sd(r1rho_799.77739910_118.078_431.000)    r1rho_799.77739910_118.078_651.200    sd(r1rho_799.77739910_118.078_651.200)    r1rho_799.77739910_118.078_800.500    sd(r1rho_799.77739910_118.078_800.500)    r1rho_799.77739910_118.078_984.000    sd(r1rho_799.77739910_118.078_984.000)    r1rho_799.77739910_124.247_1341.110    sd(r1rho_799.77739910_124.247_1341.110)    r1rho_799.77739910_130.416_1341.110    sd(r1rho_799.77739910_130.416_1341.110)    r1rho_799.77739910_130.416_1648.500    sd(r1rho_799.77739910_130.416_1648.500)    r1rho_799.77739910_130.416_800.500    sd(r1rho_799.77739910_130.416_800.500)    r1rho_799.77739910_142.754_1341.110    sd(r1rho_799.77739910_142.754_1341.110)    r1rho_799.77739910_142.754_800.500    sd(r1rho_799.77739910_142.754_800.500)    r1rho_799.77739910_179.768_1341.110    sd(r1rho_799.77739910_179.768_1341.110)    r1rho_799.77739910_241.459_1341.110    sd(r1rho_799.77739910_241.459_1341.110)    \n", 
8731              "None          5          I           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8732              "None          6          S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8733              "None          8          S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8734              "None          9          A           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8735              "None          10         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8736              "None          11         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8737              "None          12         D           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8738              "None          13         L           None        N                1.83827367612531                   None                                           1.79015307643158                   None                                            2.2768687598681                  None                                          2.08461171779445                  None                                          2.00120623474388                  None                                          1.92825070277699                  None                                          1.47212860033516                   None                                           1.12978017906854                   None                                           1.20415336139956                   None                                          0.901691390796334                  None                                         0.687390207543568                   None                                          0.455635480573046                  None                                         0.281637123971289                   None                                          0.138259661766539                   None                                       \n", 
8739              "None          14         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8740              "None          15         R           None        N                1.58367544790673                   None                                           1.58127411936947                   None                                           1.61085209029811                  None                                          1.59731540507347                  None                                          1.59237108385522                  None                                          1.58834866344307                  None                                           1.2251048782537                   None                                          0.938142786712004                   None                                           1.03297495592991                   None                                          0.683284686224254                  None                                         0.594447788256641                   None                                          0.383528609383686                  None                                         0.262780814059893                   None                                          0.133469839450564                   None                                       \n", 
8741              "None          16         T           None        N                1.40984232256624                   None                                           1.43947245672073                   None                                           1.10299856647417                  None                                          1.24811470332083                  None                                          1.30521602599932                  None                                          1.35302443831853                  None                                          1.07923777467974                   None                                          0.833345927788896                   None                                          0.934350308974616                   None                                          0.581325254389991                  None                                         0.543659670184793                   None                                          0.346238480454282                  None                                         0.251454336191817                   None                                          0.130436714663781                   None                                       \n", 
8742              "None          17         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8743              "None          18         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8744              "None          19         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8745              "None          21         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8746              "None          24         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8747              "None          25         Q           None        N                1.81569700258844                   None                                           1.77137827615015                   None                                           2.23175875585624                  None                                          2.04612705363098                  None                                           1.9673155780155                  None                                          1.89908711012298                  None                                          1.44829660124856                   None                                           1.11023386429581                   None                                           1.18716091371256                   None                                          0.877306975624962                  None                                         0.677790118853413                   None                                          0.447932002242236                  None                                         0.279785379050945                   None                                          0.137802891887767                   None                                       \n", 
8748              "None          26         Q           None        N                1.61128821168674                   None                                           1.60374392042003                   None                                           1.69619923953765                  None                                          1.65403989292986                  None                                          1.63856717205868                  None                                          1.62595755714564                  None                                          1.24977859227795                   None                                          0.956353494917591                   None                                           1.04972090035774                   None                                          0.702164059520172                  None                                         0.603227813742091                   None                                          0.390116910781037                  None                                         0.264658552037535                   None                                          0.133960994297096                   None                                       \n", 
8749              "None          27         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8750              "None          28         Q           None        N                1.65182797011356                   None                                           1.63676707684161                   None                                           1.81830827892972                  None                                           1.7365089711986                  None                                          1.70601955220877                  None                                          1.68102938663686                  None                                          1.28685736157369                   None                                          0.984047498595701                   None                                            1.0749792109454                   None                                          0.731585685663053                  None                                         0.616577997665602                   None                                          0.400219205533665                  None                                         0.267471993812649                   None                                          0.134690869499646                   None                                       \n", 
8751              "None          29         V           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8752              "None          30         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8753              "None          31         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8754              "None          32         I           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8755              "None          33         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8756              "None          34         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8757              "None          35         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8758              "None          36         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8759              "None          38         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8760              "None          39         L           None        N                1.76426439181176                   None                                           1.72885318885161                   None                                           2.11826300085737                  None                                          1.95430201082222                  None                                          1.88794717058464                  None                                          1.83172922971397                  None                                          1.39549951193417                   None                                           1.06783946148624                   None                                           1.14997013232702                   None                                          0.826128785942585                  None                                         0.657105386950171                   None                                          0.431542911580536                  None                                         0.275725736430539                   None                                          0.136791385554619                   None                                       \n", 
8761              "None          40         M           None        N                 1.5521741199158                   None                                           1.55564594516135                   None                                           1.51290906497298                  None                                          1.53245929150759                  None                                          1.53960430408466                  None                                          1.54541832596591                  None                                          1.19750223001929                   None                                          0.917959090226757                   None                                           1.01428385962747                   None                                          0.662779584695967                  None                                         0.584708929219264                   None                                          0.376271266885303                  None                                         0.260671619214194                   None                                          0.132914250767089                   None                                       \n", 
8762              "None          41         A           None        N                1.68339451828261                   None                                           1.66252964414082                   None                                           1.90911961276946                  None                                          1.79959323497326                  None                                          1.75801925517113                  None                                          1.72370710837265                  None                                          1.31646868936419                   None                                           1.00647189763597                   None                                           1.09525348649914                   None                                           0.75605702767542                  None                                         0.627395557358039                   None                                          0.408481831044309                  None                                         0.269716174238842                   None                                          0.135267948387412                   None                                       \n", 
8763              "None          42         A           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8764              "None          43         F           None        N                1.58506597154432                   None                                           1.58240542750303                   None                                           1.61517196062351                  None                                          1.60017740004898                  None                                          1.59469990835425                  None                                          1.59024353162528                  None                                          1.22633651794829                   None                                          0.939047922181951                   None                                           1.03380990731605                   None                                          0.684214484755514                  None                                         0.594884298549546                   None                                          0.383855128702894                  None                                         0.262874695048502                   None                                           0.13349447283116                   None                                       \n", 
8765              "None          44         I           None        N                1.57575471961837                   None                                           1.57483015671791                   None                                           1.58622388390755                  None                                          1.58100758841935                  None                                          1.57910319967536                  None                                          1.57755415552211                  None                                          1.21811077066835                   None                                          0.933010299763027                   None                                           1.02823520295828                   None                                           0.67802911457195                  None                                         0.591972285081647                   None                                          0.381678892926696                  None                                         0.262247347241724                   None                                          0.133329708422379                   None                                       \n", 
8766              "None          45         K           None        N                1.77147501495754                   None                                           1.73479633022489                   None                                           2.13509660780385                  None                                          1.96751045408372                  None                                          1.89924480319914                  None                                          1.84124387452692                  None                                          1.40277881643715                   None                                           1.07361367582571                   None                                           1.15506365550891                   None                                          0.832963505534767                  None                                         0.659913187081268                   None                                          0.433751178249555                  None                                         0.276282572106685                   None                                           0.13693095791902                   None                                       \n", 
8767              "None          46         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8768              "None          48         T           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8769              "None          49         A           None        N                2.00297059962685                   None                                           1.92978318052058                   None                                           2.53305709323468                  None                                          2.33052197276846                  None                                          2.22870514722639                  None                                          2.13201782446864                  None                                           1.6587904412969                   None                                           1.29333162369472                   None                                           1.34311052758116                   None                                           1.12559033900783                  None                                         0.770195063841652                   None                                          0.524846264860003                  None                                         0.296857751274362                   None                                          0.141908833673671                   None                                       \n", 
8770              "None          50         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8771              "None          51         Y           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8772              "None          52         V           None        N                1.82421571143794                   None                                           1.77845404105203                   None                                           2.24910726268822                  None                                          2.06078232916932                  None                                          1.98017451806059                  None                                          1.91012195713554                  None                                          1.45724107606646                   None                                           1.11753869321304                   None                                           1.19352234944057                   None                                          0.886361068343012                  None                                         0.681372607920812                   None                                          0.450799407357501                  None                                         0.280478735779163                   None                                          0.137974257665877                   None                                       \n", 
8773              "None          53         A           None        N                2.05019708195234                   None                                           1.97089957318506                   None                                           2.58789168363698                  None                                          2.39027806684801                  None                                          2.28731354878582                  None                                           2.1872118539319                  None                                           1.7165709935896                   None                                           1.34832362477229                   None                                           1.38879751095815                   None                                            1.2085314357749                  None                                         0.799450059125864                   None                                          0.550583841461621                  None                                          0.30195492609136                   None                                          0.143090604877102                   None                                       \n", 
8774              "None          54         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8775              "None          55         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8776              "None          57         G           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8777              "None          58         M           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8778              "None          59         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n" 
8779          ] 
8780          # Check the created theta file. 
8781          lines = theta_file.readlines() 
8782          for i in range(len(lines)): 
8783              # Test lines starting with # 
8784              if theta_result[i][0] == "#": 
8785                  self.assertEqual(theta_result[i], lines[i]) 
8786              # If the line is equal each other, make a line comparison. This should catch lines with None values. 
8787              if theta_result[i] == lines[i]: 
8788                  self.assertEqual(theta_result[i], lines[i]) 
8789              # If the line is not equal each other, make a slower comparison of values. 
8790              else: 
8791                  # Print lines if they don't match. To help find differences. 
8792                  print(theta_result[i]) 
8793                  print(lines[i]) 
8794   
8795                  # First test first 62 characters containing spin information 
8796                  self.assertEqual(theta_result[i][:62], lines[i][:62]) 
8797   
8798                  # Make a string split after 62 characters. Select each second element, so None values are skipped. 
8799                  theta_result_s = theta_result[i][62:].split()[::2] 
8800                  print(theta_result_s ) 
8801                  lines_s = lines[i][62:].split()[::2] 
8802                  print(lines_s) 
8803                  # Loop over the value elements 
8804                  for j in range(len(lines_s)): 
8805                      print(theta_result_s[j], lines_s[j]) 
8806                      # Assume a precision to digits. 
8807                      self.assertAlmostEqual(float(theta_result_s[j]), float(lines_s[j]), 14) 
8808   
8809          # Close file 
8810          theta_file.close() 
8811   
8812          w_eff_file = open(w_eff_filepath, 'r') 
8813          w_eff_result = [ 
8814              "# Parameter description:  Effective field in rotating frame : ( w_eff = sqrt(Omega^2 + w_1^2) ) (rad.s^-1).\n", 
8815              "#\n", 
8816              "# mol_name    res_num    res_name    spin_num    spin_name    r1rho_799.77739910_118.078_1341.110    sd(r1rho_799.77739910_118.078_1341.110)    r1rho_799.77739910_118.078_1648.500    sd(r1rho_799.77739910_118.078_1648.500)    r1rho_799.77739910_118.078_431.000    sd(r1rho_799.77739910_118.078_431.000)    r1rho_799.77739910_118.078_651.200    sd(r1rho_799.77739910_118.078_651.200)    r1rho_799.77739910_118.078_800.500    sd(r1rho_799.77739910_118.078_800.500)    r1rho_799.77739910_118.078_984.000    sd(r1rho_799.77739910_118.078_984.000)    r1rho_799.77739910_124.247_1341.110    sd(r1rho_799.77739910_124.247_1341.110)    r1rho_799.77739910_130.416_1341.110    sd(r1rho_799.77739910_130.416_1341.110)    r1rho_799.77739910_130.416_1648.500    sd(r1rho_799.77739910_130.416_1648.500)    r1rho_799.77739910_130.416_800.500    sd(r1rho_799.77739910_130.416_800.500)    r1rho_799.77739910_142.754_1341.110    sd(r1rho_799.77739910_142.754_1341.110)    r1rho_799.77739910_142.754_800.500    sd(r1rho_799.77739910_142.754_800.500)    r1rho_799.77739910_179.768_1341.110    sd(r1rho_799.77739910_179.768_1341.110)    r1rho_799.77739910_241.459_1341.110    sd(r1rho_799.77739910_241.459_1341.110)    \n", 
8817              "None          5          I           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8818              "None          6          S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8819              "None          8          S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8820              "None          9          A           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8821              "None          10         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8822              "None          11         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8823              "None          12         D           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8824              "None          13         L           None        N                8737.12883908829                   None                                           10612.1226552258                   None                                           3558.93734069587                  None                                          4698.27194621826                  None                                          5534.46153956037                  None                                          6599.82570817753                  None                                          8467.62674839481                   None                                           9318.00441649087                   None                                           11095.2662520767                   None                                           6412.33580591254                  None                                          13279.9803044242                   None                                            11430.254637056                  None                                          30318.7268264644                   None                                           61141.1080046448                   None                                       \n", 
8825              "None          14         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8826              "None          15         R           None        N                8427.14155005377                   None                                           10358.3995676635                   None                                           2710.22680763322                  None                                          4093.04942975722                  None                                          5030.86065069262                  None                                          6183.60685459024                  None                                          8956.28403254202                   None                                           10448.6627754369                   None                                           12060.4428066937                   None                                           7966.64282975241                  None                                          15045.8392092364                   None                                           13441.3586252373                  None                                          32438.4764809909                   None                                           63321.5201471181                   None                                       \n", 
8827              "None          16         T           None        N                 8536.7818857229                   None                                            10447.792678989                   None                                           3034.01707453628                  None                                           4314.2767521567                  None                                          5212.43600885913                  None                                          6332.21319855067                  None                                          9558.14311447582                   None                                           11384.2336494604                   None                                           12879.4604966293                   None                                           9159.34604475399                  None                                          16290.1746838959                   None                                           14821.0200530829                  None                                          33866.5933527757                   None                                           64785.3205696403                   None                                       \n", 
8828              "None          17         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8829              "None          18         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8830              "None          19         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8831              "None          21         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8832              "None          24         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8833              "None          25         Q           None        N                8685.60895531182                   None                                           10569.7459677762                   None                                           3430.51272680396                  None                                          4601.75421490393                  None                                          5452.76508815826                  None                                          6531.46859076009                  None                                          8490.06475886501                   None                                           9406.58372902508                   None                                           11169.7602637607                   None                                           6540.38696356753                  None                                          13437.7348017798                   None                                           11613.1632549021                  None                                          30514.0741594726                   None                                           61342.4792156782                   None                                       \n", 
8834              "None          26         Q           None        N                8433.35533683544                   None                                           10363.4554631194                   None                                           2729.48656005151                  None                                          4105.82770792005                  None                                          5041.26238350827                  None                                          6192.07245313098                  None                                          8880.08366342131                   None                                           10312.6868786802                   None                                           11942.8320576165                   None                                           7787.44854491812                  None                                          14853.4987024375                   None                                           13225.7048162038                  None                                          32213.6690023282                   None                                           63090.7407990801                   None                                       \n", 
8835              "None          27         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8836              "None          28         Q           None        N                8454.18308422202                   None                                           10380.4112885894                   None                                           2793.17494362899                  None                                          4148.43953208179                  None                                          5076.02756135055                  None                                          6220.40920270029                  None                                          8777.91538040813                   None                                           10118.8737706315                   None                                           11775.8792998529                   None                                           7528.90766101027                  None                                          14572.4015102398                   None                                            12909.211050939                  None                                          31882.8171856889                   None                                           62750.9120842199                   None                                       \n", 
8837              "None          29         V           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8838              "None          30         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8839              "None          31         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8840              "None          32         I           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8841              "None          33         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8842              "None          34         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8843              "None          35         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8844              "None          36         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8845              "None          38         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8846              "None          39         L           None        N                 8586.6405431352                   None                                           10488.5710521378                   None                                           3171.59430904777                  None                                          4412.11227722123                  None                                          5293.69814015286                  None                                          6399.27143075725                  None                                          8557.58926327909                   None                                           9617.45773774313                   None                                           11347.9169998729                   None                                           6840.20010813426                  None                                          13795.1250622375                   None                                           12024.9041436853                  None                                           30951.651485352                   None                                           61793.2130509111                   None                                       \n", 
8847              "None          40         M           None        N                8427.90394711227                   None                                           10359.0198301036                   None                                           2712.59646573568                  None                                          4094.61889210019                  None                                          5032.13762965554                  None                                           6184.6458240746                  None                                          9049.68452800053                   None                                           10607.7913029633                   None                                           12198.5639821231                   None                                           8174.23271685285                  None                                          15266.4924700447                   None                                           13687.9010998756                  None                                          32694.9043143038                   None                                           63584.6371927381                   None                                       \n", 
8848              "None          41         A           None        N                8480.14299737436                   None                                           10401.5648897003                   None                                           2870.79081440785                  None                                          4201.09083283266                  None                                          5119.14733505123                  None                                          6255.64579267482                  None                                          8706.50768957471                   None                                           9972.71017314947                   None                                           11650.5225246067                   None                                           7331.28858930568                  None                                          14354.1616183112                   None                                           12662.3378547029                  None                                          31623.9195264738                   None                                           62484.8290612112                   None                                       \n", 
8849              "None          42         A           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8850              "None          43         F           None        N                8427.30062786474                   None                                           10358.5289868368                   None                                            2710.7214015056                  None                                          4093.37694357637                  None                                          5031.12711571215                  None                                          6183.82364721878                  None                                          8952.31975962078                   None                                           10441.7375680915                   None                                           12054.4435931163                   None                                           7957.55789315654                  None                                          15036.1316712316                   None                                           13430.4914212645                  None                                          32427.1596037519                   None                                           63309.9050677925                   None                                       \n", 
8851              "None          44         I           None        N                8426.54623319716                   None                                           10357.9152496503                   None                                            2708.3751705368                  None                                          4091.82359712664                  None                                          5029.86337809029                  None                                          6182.79552045043                  None                                          8979.12144335458                   None                                           10488.2688526334                   None                                           12094.7720286018                   None                                           8018.51779989075                  None                                          15101.1843990883                   None                                           13503.2816173444                  None                                          32502.9389163062                   None                                           63387.6763306952                   None                                       \n", 
8852              "None          45         K           None        N                8599.01176345321                   None                                           10498.7013581079                   None                                           3204.93649737055                  None                                          4436.14046641897                  None                                          5313.74138343704                  None                                          6415.86177652694                  None                                          8546.79665373249                   None                                           9587.16245449134                   None                                           11322.2529042385                   None                                           6797.53838612575                  None                                          13745.1536613763                   None                                           11967.5433300612                  None                                          30890.8603419261                   None                                           61730.6213936947                   None                                       \n", 
8853              "None          46         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8854              "None          48         T           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8855              "None          49         A           None        N                9279.63849130869                   None                                           11063.0654625247                   None                                           4737.11992391463                  None                                          5643.40583860235                  None                                          6356.45614406507                  None                                          7302.87406141381                  None                                          8459.17105047661                   None                                           8761.54554569995                   None                                           10632.2343488142                   None                                           5572.92782399155                  None                                          12102.1714908775                   None                                           10037.6988885228                  None                                          28806.6916858172                   None                                           59579.0348769179                   None                                       \n", 
8856              "None          50         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8857              "None          51         Y           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8858              "None          52         V           None        N                8704.45610117774                   None                                           10585.2389163429                   None                                            3477.9549539207                  None                                          4637.22923167743                  None                                          5482.73656118686                  None                                           6556.5108895527                  None                                          8481.06470969555                   None                                           9372.86414918436                   None                                           11141.3782476763                   None                                           6491.79686536093                  None                                          13378.2843939736                   None                                           11544.3205736882                  None                                            30440.62308788                   None                                           61266.7742546508                   None                                       \n", 
8859              "None          53         A           None        N                9497.02860450276                   None                                           11246.0339326126                   None                                           5149.96766581255                  None                                          5994.15475647208                  None                                          6669.81232845336                  None                                          7577.19152075731                  None                                          8516.77431951689                   None                                           8639.36099840319                   None                                           10531.7750336522                   None                                           5378.79193153767                  None                                          11752.8060152439                   None                                           9613.59939949642                  None                                          28334.9153747994                   None                                           59090.2988815445                   None                                       \n", 
8860              "None          54         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8861              "None          55         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8862              "None          57         G           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8863              "None          58         M           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8864              "None          59         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n" 
8865          ] 
8866          # Check the created w_eff file. 
8867          lines = w_eff_file.readlines() 
8868          for i in range(len(lines)): 
8869              # Test lines starting with # 
8870              if w_eff_result[i][0] == "#": 
8871                  self.assertEqual(w_eff_result[i], lines[i]) 
8872              # If the line is equal each other, make a line comparison. This should catch lines with None values. 
8873              if w_eff_result[i] == lines[i]: 
8874                  self.assertEqual(w_eff_result[i], lines[i]) 
8875              # If the line is not equal each other, make a slower comparison of values. 
8876              else: 
8877                  # Print lines if they don't match. To help find differences. 
8878                  print(w_eff_result[i]) 
8879                  print(lines[i]) 
8880   
8881                  # First test first 62 characters containing spin information 
8882                  self.assertEqual(w_eff_result[i][:62], lines[i][:62]) 
8883   
8884                  # Make a string split after 62 characters. Select each second element, so None values are skipped. 
8885                  w_eff_result_s = w_eff_result[i][62:].split()[::2] 
8886                  print(w_eff_result_s ) 
8887                  lines_s = lines[i][62:].split()[::2] 
8888                  print(lines_s) 
8889                  # Loop over the value elements 
8890                  for j in range(len(lines_s)): 
8891                      print(w_eff_result_s[j], lines_s[j]) 
8892                      # Assume a precision to digits. 
8893                      self.assertAlmostEqual(float(w_eff_result_s[j]), float(lines_s[j]), 14) 
8894   
8895          # Close file 
8896          w_eff_file.close() 
8897   
8898   
8899 -    def verify_estimate_r2eff_err_compare_mc(self): 
8900          """Test the user function for estimating R2eff errors from exponential curve fitting, and compare it with Monte-Carlo simulations. 
8901   
8902          This follows Task 7822. 
8903          U{task #7822<https://gna.org/task/index.php?7822>}: Implement user function to estimate R2eff and associated errors for exponential curve fitting. 
8904   
8905          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
8906          Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
8907          """ 
8908   
8909          # Load the data. 
8910          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013'+sep 
8911   
8912          # Set pipe name, bundle and type. 
8913          pipe_name = 'base pipe' 
8914          pipe_bundle = 'relax_disp' 
8915          pipe_type = 'relax_disp' 
8916   
8917          # Create the data pipe. 
8918          self.interpreter.pipe.create(pipe_name=pipe_name, bundle=pipe_bundle, pipe_type=pipe_type) 
8919   
8920          file = data_path + '1_setup_r1rho_GUI.py' 
8921          self.interpreter.script(file=file, dir=None) 
8922   
8923          # Deselect all spins. 
8924          self.interpreter.deselect.spin(spin_id=':1-100', change_all=False) 
8925   
8926          # Select one spin. 
8927          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
8928   
8929          # Set the model. 
8930          self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
8931   
8932          # Check if intensity errors have already been calculated. 
8933          check_intensity_errors() 
8934   
8935          # Do a grid search. 
8936          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=11, constraints=True, verbosity=1) 
8937   
8938          # Set algorithm. 
8939          min_algor = 'Newton' 
8940          constraints = True 
8941          if constraints: 
8942              min_options = ('%s'%(min_algor),) 
8943              #min_algor = 'Log barrier' 
8944              min_algor = 'Method of Multipliers' 
8945              scaling_matrix = assemble_scaling_matrix(scaling=True) 
8946   
8947              # Collect spins 
8948              all_spin_ids = [] 
8949              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
8950                  all_spin_ids.append(spin_id) 
8951   
8952              spins = spin_ids_to_containers(all_spin_ids[:1]) 
8953   
8954              # Get constraints 
8955              A, b = linear_constraints(spins=spins, scaling_matrix=scaling_matrix[0]) 
8956          else: 
8957              min_options = () 
8958              A, b = None, None 
8959          min_options = () 
8960          sim_boot = 200 
8961          scaling_list = [1.0, 1.0] 
8962   
8963          # Minimise. 
8964          self.interpreter.minimise.execute(min_algor=min_algor, constraints=constraints, verbosity=1) 
8965   
8966          # Loop over old err attributes. 
8967          err_attr_list = ['r2eff_err', 'i0_err'] 
8968   
8969          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
8970              # Loop over old err attributes. 
8971              for err_attr in err_attr_list: 
8972                  if hasattr(cur_spin, err_attr): 
8973                      delattr(cur_spin, err_attr) 
8974   
8975          # Collect the estimation data from boot. 
8976          my_dic = {} 
8977          param_key_list = [] 
8978          est_keys = [] 
8979          est_key = '-2' 
8980          est_keys.append(est_key) 
8981          spin_id_list = [] 
8982   
8983          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
8984              # Add key to dic. 
8985              my_dic[spin_id] = {} 
8986   
8987              # Add key for estimate. 
8988              my_dic[spin_id][est_key] = {} 
8989   
8990              # Add spin key to list. 
8991              spin_id_list.append(spin_id) 
8992   
8993              # Generate spin string. 
8994              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
8995   
8996              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
8997                  # Generate the param_key. 
8998                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
8999   
9000                  # Append key. 
9001                  param_key_list.append(param_key) 
9002   
9003                  # Add key to dic. 
9004                  my_dic[spin_id][est_key][param_key] = {} 
9005   
9006                  values = [] 
9007                  errors = [] 
9008                  times = [] 
9009                  for time in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point): 
9010                      values.append(average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time)) 
9011                      errors.append(average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, error=True)) 
9012                      times.append(time) 
9013   
9014                  # Convert to numpy array. 
9015                  values = asarray(values) 
9016                  errors = asarray(errors) 
9017                  times = asarray(times) 
9018   
9019                  r2eff = getattr(cur_spin, 'r2eff')[param_key] 
9020                  i0 = getattr(cur_spin, 'i0')[param_key] 
9021   
9022                  R_m_sim_l = [] 
9023                  I0_m_sim_l = [] 
9024                  for j in range(sim_boot): 
9025                      if j in range(0, 100000, 100): 
9026                          print("Simulation %i"%j) 
9027                      # Start minimisation. 
9028   
9029                      # Produce errors 
9030                      I_err = [] 
9031                      for j, error in enumerate(errors): 
9032                          I_error = gauss(values[j], error) 
9033                          I_err.append(I_error) 
9034                      # Convert to numpy array. 
9035                      I_err = asarray(I_err) 
9036   
9037                      x0 = [r2eff, i0] 
9038                      setup(num_params=len(x0), num_times=len(times), values=I_err, sd=errors, relax_times=times, scaling_matrix=scaling_list) 
9039   
9040                      # Ref input. 
9041                      #def generic_minimise(func=None, dfunc=None, d2func=None, args=(), x0=None, min_algor=None, min_options=None, func_tol=1e-25, grad_tol=None, maxiter=1e6, A=None, b=None, l=None, u=None, c=None, dc=None, d2c=None, print_flag=0, print_prefix="", full_output=False): 
9042                      # l=l, u=u, c=c, dc=dc, d2c=d2c 
9043                      # l: Lower bound constraint vector (l <= x <= u). 
9044                      # u: Upper bound constraint vector (l <= x <= u). 
9045                      # c: User supplied constraint function. 
9046                      # dc: User supplied constraint gradient function. 
9047                      params_minfx_sim_j, chi2_minfx_sim_j, iter_count, f_count, g_count, h_count, warning = generic_minimise(func=func, dfunc=dfunc, d2func=d2func, args=(), x0=x0, min_algor=min_algor, min_options=min_options, A=A, b=b, full_output=True, print_flag=0) 
9048   
9049                      R_m_sim_j, I0_m_sim_j = params_minfx_sim_j 
9050                      R_m_sim_l.append(R_m_sim_j) 
9051                      I0_m_sim_l.append(I0_m_sim_j) 
9052   
9053                  # Get stats on distribution. 
9054                  sigma_R_sim = std(asarray(R_m_sim_l), ddof=1) 
9055                  sigma_I0_sim = std(asarray(I0_m_sim_l), ddof=1) 
9056                  my_dic[spin_id][est_key][param_key]['r2eff_err'] = sigma_R_sim 
9057                  my_dic[spin_id][est_key][param_key]['i0_err'] = sigma_I0_sim 
9058   
9059          # Estimate R2eff errors. 
9060          self.interpreter.relax_disp.r2eff_err_estimate() 
9061   
9062          est_key = '-1' 
9063          est_keys.append(est_key) 
9064   
9065          # Collect data. 
9066          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9067              # Add key for estimate. 
9068              my_dic[spin_id][est_key] = {} 
9069   
9070              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
9071                  # Generate the param_key. 
9072                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
9073   
9074                  # Add key to dic. 
9075                  my_dic[spin_id][est_key][param_key] = {} 
9076   
9077                  # Get the value. 
9078                  # Loop over err attributes. 
9079                  for err_attr in err_attr_list: 
9080                      if hasattr(cur_spin, err_attr): 
9081                          get_err_attr = getattr(cur_spin, err_attr)[param_key] 
9082                      else: 
9083                          get_err_attr = 0.0 
9084   
9085                      # Save to dic. 
9086                      my_dic[spin_id][est_key][param_key][err_attr] = get_err_attr 
9087   
9088   
9089          # Make Carlo Simulations number 
9090          mc_number_list = list(range(0, 1000, 250)) 
9091   
9092          sim_attr_list = ['chi2_sim', 'f_count_sim', 'g_count_sim', 'h_count_sim', 'i0_sim', 'iter_sim', 'peak_intensity_sim', 'r2eff_sim', 'select_sim', 'warning_sim'] 
9093   
9094          # Loop over the Monte Carlo simulations: 
9095          for number in mc_number_list: 
9096              # First delete old simulations. 
9097              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9098                  # Loop over old err attributes. 
9099                  for err_attr in err_attr_list: 
9100                      if hasattr(cur_spin, err_attr): 
9101                          delattr(cur_spin, err_attr) 
9102   
9103                  # Loop over the simulated attributes. 
9104                  for sim_attr in sim_attr_list: 
9105                      if hasattr(cur_spin, sim_attr): 
9106                          delattr(cur_spin, sim_attr) 
9107   
9108              self.interpreter.monte_carlo.setup(number=number) 
9109              self.interpreter.monte_carlo.create_data() 
9110              self.interpreter.monte_carlo.initial_values() 
9111              self.interpreter.minimise.execute(min_algor=min_algor, constraints=constraints) 
9112              self.interpreter.eliminate() 
9113              self.interpreter.monte_carlo.error_analysis() 
9114   
9115              est_key = '%i'%number 
9116              est_keys.append(est_key) 
9117   
9118              # Collect data. 
9119              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9120                  # Add key for estimate. 
9121                  my_dic[spin_id][est_key] = {} 
9122   
9123                  for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
9124                      # Generate the param_key. 
9125                      param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
9126   
9127                      # Add key to dic. 
9128                      my_dic[spin_id][est_key][param_key] = {} 
9129   
9130                      # Get the value. 
9131                      # Loop over err attributes. 
9132                      for err_attr in err_attr_list: 
9133                          if hasattr(cur_spin, err_attr): 
9134                              get_err_attr = getattr(cur_spin, err_attr)[param_key] 
9135                          else: 
9136                              get_err_attr = 0.0 
9137   
9138                          # Save to dic. 
9139                          my_dic[spin_id][est_key][param_key][err_attr] = get_err_attr 
9140   
9141          # Set what to extract. 
9142          err_attr = err_attr_list[0] 
9143   
9144          # Define list with text. 
9145          text_list = [] 
9146   
9147          # Now loop through the data. 
9148          for spin_id in spin_id_list: 
9149              for est_key in est_keys: 
9150                  # Define list to pickup data. 
9151                  r2eff_err_list = [] 
9152   
9153                  for param_key in param_key_list: 
9154                      # Get the value. 
9155                      r2eff_err = my_dic[spin_id][est_key][param_key][err_attr] 
9156   
9157                      # Add to list. 
9158                      r2eff_err_list.append(r2eff_err) 
9159   
9160                  # Sum the list 
9161                  sum_array = sum(array(r2eff_err_list)) 
9162   
9163                  # Join floats to string. 
9164                  r2eff_err_str = " ".join(format(x, "2.3f") for x in r2eff_err_list) 
9165   
9166                  # Define print string. 
9167                  text = "%8s %s sum= %2.3f" % (est_key, r2eff_err_str, sum_array) 
9168                  text_list.append(text) 
9169   
9170   
9171          # Now print. 
9172          filepath = NamedTemporaryFile(delete=False).name 
9173          # Open the files for testing. 
9174          w_file = open(filepath, 'w') 
9175   
9176          print("Printing the estimated R2eff error as function of estimation from Co-variance and number of Monte-Carlo simulations.") 
9177   
9178          for text in text_list: 
9179              # Print. 
9180              print(text) 
9181   
9182              # Write to file. 
9183              w_file.write(text+"\n") 
9184   
9185          # Close files 
9186          w_file.close() 
9187   
9188          print("Filepath is: %s"%filepath) 
9189          print("Start 'gnuplot' and write:") 
9190          print("set term dumb") 
9191          print("plot '%s' using 1:17 title 'R2eff error as function of MC number' w linespoints "%filepath) 
9192   
9193   
9194 -    def verify_r1rho_kjaergaard_missing_r1(self, models=None, result_dir_name=None, r2eff_estimate=None): 
9195          """Verification of test_r1rho_kjaergaard_missing_r1.""" 
9196   
9197          # Check the kex value of residue 52 
9198          #self.assertAlmostEqual(cdp.mol[0].res[41].spin[0].kex, ds.ref[':52@N'][6]) 
9199   
9200          # Print results for each model. 
9201          print("\n\n################") 
9202          print("Printing results") 
9203          print("################\n") 
9204          for model in models: 
9205              # Skip R2eff model. 
9206              if model == MODEL_R2EFF: 
9207                  continue 
9208   
9209              # Switch to pipe. 
9210              self.interpreter.pipe.switch(pipe_name='%s - relax_disp' % (model)) 
9211              print("\nModel: %s" % (model)) 
9212   
9213              # Loop over the spins. 
9214              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9215                  # Generate spin string. 
9216                  spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
9217   
9218                  # Loop over the parameters. 
9219                  print("Optimised parameters for spin: %s" % (spin_string)) 
9220                  for param in cur_spin.params + ['chi2']: 
9221                      # Get the value. 
9222                      if param in ['r1', 'r2']: 
9223                          for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True): 
9224                              # Generate the R20 key. 
9225                              r20_key = generate_r20_key(exp_type=exp_type, frq=frq) 
9226   
9227                              # Get the value. 
9228                              value = getattr(cur_spin, param)[r20_key] 
9229   
9230                              # Print value. 
9231                              print("%-10s %-6s %-6s %3.8f" % ("Parameter:", param, "Value:", value)) 
9232   
9233                              # Compare values. 
9234                              if spin_id == ':52@N': 
9235                                  if param == 'r1': 
9236                                      if model == MODEL_NOREX: 
9237                                          if r2eff_estimate == 'direct': 
9238                                              self.assertAlmostEqual(value, 1.46138805) 
9239                                          elif r2eff_estimate == 'MC2000': 
9240                                              self.assertAlmostEqual(value, 1.46328102) 
9241                                          elif r2eff_estimate == 'chi2_pyt': 
9242                                              self.assertAlmostEqual(value, 1.43820629) 
9243                                      elif model == MODEL_DPL94: 
9244                                          if r2eff_estimate == 'direct': 
9245                                              self.assertAlmostEqual(value, 1.44845742) 
9246                                          elif r2eff_estimate == 'MC2000': 
9247                                              self.assertAlmostEqual(value, 1.45019848) 
9248                                          elif r2eff_estimate == 'chi2_pyt': 
9249                                              self.assertAlmostEqual(value, 1.44666512) 
9250                                      elif model == MODEL_TP02: 
9251                                          if r2eff_estimate == 'direct': 
9252                                              self.assertAlmostEqual(value, 1.54354392) 
9253                                          elif r2eff_estimate == 'MC2000': 
9254                                              self.assertAlmostEqual(value, 1.54352369) 
9255                                          elif r2eff_estimate == 'chi2_pyt': 
9256                                              self.assertAlmostEqual(value, 1.55964020) 
9257                                      elif model == MODEL_TAP03: 
9258                                          if r2eff_estimate == 'direct': 
9259                                              self.assertAlmostEqual(value, 1.54356410) 
9260                                          elif r2eff_estimate == 'MC2000': 
9261                                              self.assertAlmostEqual(value, 1.54354367) 
9262                                          elif r2eff_estimate == 'chi2_pyt': 
9263                                              self.assertAlmostEqual(value, 1.55967157) 
9264                                      elif model == MODEL_MP05: 
9265                                          if r2eff_estimate == 'direct': 
9266                                              self.assertAlmostEqual(value, 1.54356416) 
9267                                          elif r2eff_estimate == 'MC2000': 
9268                                              self.assertAlmostEqual(value, 1.54354372) 
9269                                          elif r2eff_estimate == 'chi2_pyt': 
9270                                              self.assertAlmostEqual(value, 1.55967163) 
9271                                      elif model == MODEL_NS_R1RHO_2SITE: 
9272                                          if r2eff_estimate == 'direct': 
9273                                              self.assertAlmostEqual(value, 1.41359221, 5) 
9274                                          elif r2eff_estimate == 'MC2000': 
9275                                              self.assertAlmostEqual(value, 1.41321968, 5) 
9276                                          elif r2eff_estimate == 'chi2_pyt': 
9277                                              self.assertAlmostEqual(value, 1.36303129, 5) 
9278   
9279                                  elif param == 'r2': 
9280                                      if model == MODEL_NOREX: 
9281                                          if r2eff_estimate == 'direct': 
9282                                              self.assertAlmostEqual(value, 11.48392439) 
9283                                          elif r2eff_estimate == 'MC2000': 
9284                                              self.assertAlmostEqual(value, 11.48040934) 
9285                                          elif r2eff_estimate == 'chi2_pyt': 
9286                                              self.assertAlmostEqual(value, 11.47224488) 
9287                                      elif model == MODEL_DPL94: 
9288                                          if r2eff_estimate == 'direct': 
9289                                              self.assertAlmostEqual(value, 10.15688372, 6) 
9290                                          elif r2eff_estimate == 'MC2000': 
9291                                              self.assertAlmostEqual(value, 10.16304887, 6) 
9292                                          elif r2eff_estimate == 'chi2_pyt': 
9293                                              self.assertAlmostEqual(value, 9.20037797, 6) 
9294                                      elif model == MODEL_TP02: 
9295                                          if r2eff_estimate == 'direct': 
9296                                              self.assertAlmostEqual(value, 9.72654896, 6) 
9297                                          elif r2eff_estimate == 'MC2000': 
9298                                              self.assertAlmostEqual(value, 9.72772726, 6) 
9299                                          elif r2eff_estimate == 'chi2_pyt': 
9300                                              self.assertAlmostEqual(value, 9.53948340, 6) 
9301                                      elif model == MODEL_TAP03: 
9302                                          if r2eff_estimate == 'direct': 
9303                                              self.assertAlmostEqual(value, 9.72641887, 6) 
9304                                          elif r2eff_estimate == 'MC2000': 
9305                                              self.assertAlmostEqual(value, 9.72759374, 6) 
9306                                          elif r2eff_estimate == 'chi2_pyt': 
9307                                              self.assertAlmostEqual(value, 9.53926913, 6) 
9308                                      elif model == MODEL_MP05: 
9309                                          if r2eff_estimate == 'direct': 
9310                                              self.assertAlmostEqual(value, 9.72641723, 6) 
9311                                          elif r2eff_estimate == 'MC2000': 
9312                                              self.assertAlmostEqual(value, 9.72759220, 6) 
9313                                          elif r2eff_estimate == 'chi2_pyt': 
9314                                              self.assertAlmostEqual(value, 9.53926778, 6) 
9315                                      elif model == MODEL_NS_R1RHO_2SITE: 
9316                                          if r2eff_estimate == 'direct': 
9317                                              self.assertAlmostEqual(value, 9.34531535, 5) 
9318                                          elif r2eff_estimate == 'MC2000': 
9319                                              self.assertAlmostEqual(value, 9.34602793, 5) 
9320                                          elif r2eff_estimate == 'chi2_pyt': 
9321                                              self.assertAlmostEqual(value, 9.17631409, 5) 
9322   
9323                      # For all other parameters. 
9324                      else: 
9325                          # Get the value. 
9326                          value = getattr(cur_spin, param) 
9327   
9328                          # Print value. 
9329                          print("%-10s %-6s %-6s %3.8f" % ("Parameter:", param, "Value:", value)) 
9330   
9331                          # Compare values. 
9332                          if spin_id == ':52@N': 
9333                              if param == 'phi_ex': 
9334                                  if model == MODEL_DPL94: 
9335                                      if r2eff_estimate == 'direct': 
9336                                          self.assertAlmostEqual(value, 0.07599563) 
9337                                      elif r2eff_estimate == 'MC2000': 
9338                                          self.assertAlmostEqual(value, 0.07561937) 
9339                                      elif r2eff_estimate == 'chi2_pyt': 
9340                                          self.assertAlmostEqual(value, 0.12946061) 
9341   
9342                              elif param == 'pA': 
9343                                  if model == MODEL_TP02: 
9344                                      if r2eff_estimate == 'direct': 
9345                                          self.assertAlmostEqual(value, 0.88827040) 
9346                                      elif r2eff_estimate == 'MC2000': 
9347                                          self.assertAlmostEqual(value, 0.88807487) 
9348                                      elif r2eff_estimate == 'chi2_pyt': 
9349                                          self.assertAlmostEqual(value, 0.87746233) 
9350                                  elif model == MODEL_TAP03: 
9351                                      if r2eff_estimate == 'direct': 
9352                                          self.assertAlmostEqual(value, 0.88828922) 
9353                                      elif r2eff_estimate == 'MC2000': 
9354                                          self.assertAlmostEqual(value, 0.88809318) 
9355                                      elif r2eff_estimate == 'chi2_pyt': 
9356                                          self.assertAlmostEqual(value, 0.87747558) 
9357                                  elif model == MODEL_MP05: 
9358                                      if r2eff_estimate == 'direct': 
9359                                          self.assertAlmostEqual(value, 0.88828924, 6) 
9360                                      elif r2eff_estimate == 'MC2000': 
9361                                          self.assertAlmostEqual(value, 0.88809321) 
9362                                      elif r2eff_estimate == 'chi2_pyt': 
9363                                          self.assertAlmostEqual(value, 0.87747562) 
9364                                  elif model == MODEL_NS_R1RHO_2SITE: 
9365                                      if r2eff_estimate == 'direct': 
9366                                          self.assertAlmostEqual(value, 0.94504369, 6) 
9367                                      elif r2eff_estimate == 'MC2000': 
9368                                          self.assertAlmostEqual(value, 0.94496541, 6) 
9369                                      elif r2eff_estimate == 'chi2_pyt': 
9370                                          self.assertAlmostEqual(value, 0.92084707, 6) 
9371   
9372                              elif param == 'dw': 
9373                                  if model == MODEL_TP02: 
9374                                      if r2eff_estimate == 'direct': 
9375                                          self.assertAlmostEqual(value, 1.08875840, 6) 
9376                                      elif r2eff_estimate == 'MC2000': 
9377                                          self.assertAlmostEqual(value, 1.08765638, 6) 
9378                                      elif r2eff_estimate == 'chi2_pyt': 
9379                                          self.assertAlmostEqual(value, 1.09753230, 6) 
9380                                  elif model == MODEL_TAP03: 
9381                                      if r2eff_estimate == 'direct': 
9382                                          self.assertAlmostEqual(value, 1.08837238, 6) 
9383                                      elif r2eff_estimate == 'MC2000': 
9384                                          self.assertAlmostEqual(value, 1.08726698, 6) 
9385                                      elif r2eff_estimate == 'chi2_pyt': 
9386                                          self.assertAlmostEqual(value, 1.09708821, 6) 
9387                                  elif model == MODEL_MP05: 
9388                                      if r2eff_estimate == 'direct': 
9389                                          self.assertAlmostEqual(value, 1.08837241, 6) 
9390                                      elif r2eff_estimate == 'MC2000': 
9391                                          self.assertAlmostEqual(value, 1.08726706, 6) 
9392                                      elif r2eff_estimate == 'chi2_pyt': 
9393                                          self.assertAlmostEqual(value, 1.09708832, 6) 
9394                                  elif model == MODEL_NS_R1RHO_2SITE: 
9395                                      if r2eff_estimate == 'direct': 
9396                                          self.assertAlmostEqual(value, 1.56001812, 5) 
9397                                      elif r2eff_estimate == 'MC2000': 
9398                                          self.assertAlmostEqual(value, 1.55833321, 5) 
9399                                      elif r2eff_estimate == 'chi2_pyt': 
9400                                          self.assertAlmostEqual(value, 1.36406712, 5) 
9401   
9402                              elif param == 'kex': 
9403                                  if model == MODEL_DPL94: 
9404                                      if r2eff_estimate == 'direct': 
9405                                          self.assertAlmostEqual(value/1e5, 4460.43711569/1e5, 7) 
9406                                      elif r2eff_estimate == 'MC2000': 
9407                                          self.assertAlmostEqual(value/1e5, 4419.03917195/1e5, 7) 
9408                                      elif r2eff_estimate == 'chi2_pyt': 
9409                                          self.assertAlmostEqual(value/1e5, 6790.22736344/1e5, 7) 
9410                                  elif model == MODEL_TP02: 
9411                                      if r2eff_estimate == 'direct': 
9412                                          self.assertAlmostEqual(value/1e5, 4921.28602757/1e5, 7) 
9413                                      elif r2eff_estimate == 'MC2000': 
9414                                          self.assertAlmostEqual(value/1e5, 4904.70144883/1e5, 7) 
9415                                      elif r2eff_estimate == 'chi2_pyt': 
9416                                          self.assertAlmostEqual(value/1e5, 5146.20306591/1e5, 7) 
9417                                  elif model == MODEL_TAP03: 
9418                                      if r2eff_estimate == 'direct': 
9419                                          self.assertAlmostEqual(value/1e5, 4926.42963491/1e5, 7) 
9420                                      elif r2eff_estimate == 'MC2000': 
9421                                          self.assertAlmostEqual(value/1e5, 4909.86877150/1e5, 7) 
9422                                      elif r2eff_estimate == 'chi2_pyt': 
9423                                          self.assertAlmostEqual(value/1e5, 5152.51105814/1e5, 7) 
9424                                  elif model == MODEL_MP05: 
9425                                      if r2eff_estimate == 'direct': 
9426                                          self.assertAlmostEqual(value/1e5, 4926.44236315/1e5, 7) 
9427                                      elif r2eff_estimate == 'MC2000': 
9428                                          self.assertAlmostEqual(value/1e5, 4909.88110195/1e5, 7) 
9429                                      elif r2eff_estimate == 'chi2_pyt': 
9430                                          self.assertAlmostEqual(value/1e5, 5152.52097111/1e5, 7) 
9431                                  elif model == MODEL_NS_R1RHO_2SITE: 
9432                                      if r2eff_estimate == 'direct': 
9433                                          self.assertAlmostEqual(value/1e5, 5628.66061488/1e5, 6) 
9434                                      elif r2eff_estimate == 'MC2000': 
9435                                          self.assertAlmostEqual(value/1e5, 5610.20221435/1e5, 6) 
9436                                      elif r2eff_estimate == 'chi2_pyt': 
9437                                          self.assertAlmostEqual(value/1e5, 5643.34067090/1e5, 6) 
9438   
9439                              elif param == 'chi2': 
9440                                  if model == MODEL_NOREX: 
9441                                      if r2eff_estimate == 'direct': 
9442                                          self.assertAlmostEqual(value, 848.42016907, 5) 
9443                                      elif r2eff_estimate == 'MC2000': 
9444                                          self.assertAlmostEqual(value, 3363.95829122, 5) 
9445                                      elif r2eff_estimate == 'chi2_pyt': 
9446                                          self.assertAlmostEqual(value, 5976.49946726, 5) 
9447                                  elif model == MODEL_DPL94: 
9448                                      if r2eff_estimate == 'direct': 
9449                                          self.assertAlmostEqual(value, 179.47041241) 
9450                                      elif r2eff_estimate == 'MC2000': 
9451                                          self.assertAlmostEqual(value, 710.24767560) 
9452                                      elif r2eff_estimate == 'chi2_pyt': 
9453                                          self.assertAlmostEqual(value, 612.72616697, 5) 
9454                                  elif model == MODEL_TP02: 
9455                                      if r2eff_estimate == 'direct': 
9456                                          self.assertAlmostEqual(value, 29.33882530, 6) 
9457                                      elif r2eff_estimate == 'MC2000': 
9458                                          self.assertAlmostEqual(value, 114.47142772, 6) 
9459                                      elif r2eff_estimate == 'chi2_pyt': 
9460                                          self.assertAlmostEqual(value, 250.50838162, 5) 
9461                                  elif model == MODEL_TAP03: 
9462                                      if r2eff_estimate == 'direct': 
9463                                          self.assertAlmostEqual(value, 29.29050673, 6) 
9464                                      elif r2eff_estimate == 'MC2000': 
9465                                          self.assertAlmostEqual(value, 114.27987534) 
9466                                      elif r2eff_estimate == 'chi2_pyt': 
9467                                          self.assertAlmostEqual(value, 250.04050719, 5) 
9468                                  elif model == MODEL_MP05: 
9469                                      if r2eff_estimate == 'direct': 
9470                                          self.assertAlmostEqual(value, 29.29054301, 6) 
9471                                      elif r2eff_estimate == 'MC2000': 
9472                                          self.assertAlmostEqual(value, 114.28002272) 
9473                                      elif r2eff_estimate == 'chi2_pyt': 
9474                                          self.assertAlmostEqual(value, 250.04077478, 5) 
9475                                  elif model == MODEL_NS_R1RHO_2SITE: 
9476                                      if r2eff_estimate == 'direct': 
9477                                          self.assertAlmostEqual(value, 34.44010543, 6) 
9478                                      elif r2eff_estimate == 'MC2000': 
9479                                          self.assertAlmostEqual(value, 134.14368365) 
9480                                      elif r2eff_estimate == 'chi2_pyt': 
9481                                          self.assertAlmostEqual(value, 278.55121388, 5) 
9482   
9483   
9484          # Print the final pipe. 
9485          model = 'final' 
9486          self.interpreter.pipe.switch(pipe_name='%s - relax_disp' % (model)) 
9487          print("\nFinal pipe") 
9488   
9489          # Loop over the spins. 
9490          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9491              # Generate spin string. 
9492              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
9493   
9494              # Loop over the parameters. 
9495              print("Optimised model for spin: %s" % (spin_string)) 
9496              param = 'model' 
9497   
9498              # Get the value. 
9499              value = getattr(cur_spin, param) 
9500              print("%-10s %-6s %-6s %6s" % ("Parameter:", param, "Value:", value)) 
9501   
9502   
9503          ### Now check some of the written out files. 
9504          file_names = ['r1rho_prime', 'r1'] 
9505   
9506          for file_name_i in file_names: 
9507   
9508              # Make the file name. 
9509              file_name = "%s.out" % file_name_i 
9510   
9511              # Get the file path. 
9512              file_path = get_file_path(file_name, result_dir_name + sep + model) 
9513   
9514              # Test the file exists. 
9515              print("Testing file access to: %s"%file_path) 
9516              self.assert_(access(file_path, F_OK)) 
9517   
9518              # Now open, and compare content, line by line. 
9519              file_prod = open(file_path) 
9520              lines_prod = file_prod.readlines() 
9521              file_prod.close() 
9522   
9523              # Loop over the lines. 
9524              for i, line in enumerate(lines_prod): 
9525                  # Make the string test 
9526                  line_split = line.split() 
9527   
9528                  # Continue for comment lines. 
9529                  if line_split[0] == "#": 
9530                      print(line), 
9531                      continue 
9532   
9533                  # Assign the split of the line. 
9534                  mol_name, res_num, res_name, spin_num, spin_name, val, sd_error = line_split 
9535                  print(mol_name, res_num, res_name, spin_num, spin_name, val, sd_error) 
9536   
9537                  if res_num == '52': 
9538                      # Assert that the value is not None. 
9539                      self.assertNotEqual(val, 'None') 
9540